CN113346555B - Daily rolling scheduling method considering electric quantity coordination - Google Patents

Daily rolling scheduling method considering electric quantity coordination Download PDF

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CN113346555B
CN113346555B CN202110572568.0A CN202110572568A CN113346555B CN 113346555 B CN113346555 B CN 113346555B CN 202110572568 A CN202110572568 A CN 202110572568A CN 113346555 B CN113346555 B CN 113346555B
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张晗
王秀丽
彭巧
赵文成
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Xian Jiaotong University
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Abstract

The invention belongs to the technical field of power system dispatching operation, and discloses a daily rolling optimization dispatching method considering electric quantity coordination.

Description

Daily rolling scheduling method considering electric quantity coordination
Technical Field
The invention belongs to the technical field of power system dispatching operation, relates to a power system dispatching optimization method in a power market transition environment, and particularly relates to a daily rolling dispatching method considering electric quantity coordination.
Background
Along with the large-scale grid connection of new energy sources such as wind power, photovoltaic and the like, the establishment of a power generation plan which is adaptive to the randomness and the intermittence of the output of the new energy sources becomes one of important ways for the power grid to consume the new energy sources. The new energy ultra-short-term predicted power based on rolling update is used for carrying out daily rolling scheduling on the power system, so that the problem of system unbalance caused by new energy fluctuation can be effectively balanced, and new energy consumption is promoted. With the development of the power market, the coordination problem of the planned electric quantity and various types of contract electric quantity is considered when the scheduling plan is arranged, and the current three-public scheduling mode provides new requirements of electric quantity constraint for the formulation of the daily scheduling plan. On the basis of ensuring new energy consumption, making a daily rolling scheduling strategy suitable for the current power market environment is an important subject faced by power system operators.
In the real-time scheduling operation, the actual power generation curve and the day-ahead power generation planning curve generate larger deviation due to the new energy prediction error and possible faults such as forced shutdown of the generator set; the fluctuation of new energy power generation also makes the unit output continuously corrected in the daily real-time scheduling process, greatly increases the workload of real-time scheduling, and the daily electric quantity plan of the power plant has to be changed. However, the dispatching department is used as an executor of the power generation plan, and needs to ensure that the rolling correction of the power generation plan in the day should track the power generation curve before the day as much as possible, so as to ensure the effective execution of the power generation plan before the day. Meanwhile, under the current power market environment of China, the current three-metric scheduling has stricter requirements on the electric quantity completion progress of a unit (or a power plant), and on the basis of considering economy and optimizing new energy consumption, how to flexibly and accurately consider the electric quantity progress in a daily scheduling plan and realize scheduling fairness is a research focus of daily rolling scheduling of a current power system.
At present, the current daily rolling power generation plans mostly do not consider dynamic rolling adjustment of the power completion progress, a dispatching department often relies on manual adjustment of unit power deviation, the current daily power deviation is compensated by future days, the mode lacks effective constraint of fairness, convergence of the power plant power completion progress cannot be guaranteed, and meanwhile frequent adjustment output of the unit is caused, so that operation and maintenance cost is increased.
Disclosure of Invention
The invention aims to solve the problems that how to adapt to the requirements of the electric market transition period on planned electric quantity and contract electric quantity on fairness in real-time scheduling operation, flexibly and accurately consider the electric quantity completion progress and realize rolling adjustment when scheduling the plan in a manufacturing day, obtain an intra-day unit output plan considering multi-type electric quantity coordination, and the intra-day electric quantity control of a unit is difficult to adapt to the change of the power grid operation environment and has high manual intervention dependency.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
a daily rolling scheduling method considering electric quantity coordination comprises the following steps:
step one, acquiring a power system day-ahead dispatching plan, wherein the power system day-ahead dispatching plan comprises unit start-stop and output information and an electric quantity plan which are arranged day-ahead; the electric quantity plan comprises the daily total power generation amount and the contract power generation amount of each power plant arranged in the daily scheduling plan;
step two, updating ultra-short-term new energy output power prediction and load prediction information;
step three, based on the results obtained in the step one and the step two, establishing and solving a daily optimization scheduling model considering electric quantity coordination, and rolling an electric quantity plan of a correction scheduling period to obtain a daily scheduling scheme considering electric quantity coordination in the remaining period of the day;
taking a unit start-stop and output scheme of a first time period in an intra-day scheduling scheme taking the electric quantity coordination into consideration in the remaining time period of the day as a correction scheme of the current time;
step five, judging whether 96 points are finished or not in the whole day according to the correction scheme, if not, entering the next moment, and repeating the step two to the step five; if the power supply is finished, the whole-day rolling scheduling of the day is finished, a daily scheduling plan considering the power coordination is obtained, the effective tracking of the daily power plan is finished according to the daily scheduling plan considering the power coordination, and the effectiveness and fairness of the power completion are ensured.
Further, the second step comprises the following steps: dividing 24 hours in a running day into 96 points at 15min intervals, and for a certain running time t in the day 0 Updating the current running time t 0 The state and the actual output of the machine set; for the operating time t 0 And updating the short-term power prediction and the load prediction of the new energy source in the interval from the ending time T of the current day.
Further, in the third step, a daily optimization scheduling model considering electric quantity coordination is established through the following processes:
the power coordination day-to-day optimization scheduling model is considered to minimize new energy power rejection cost, day-to-day output plan adjustment cost, day-to-day power plan deviation cost and day-to-day power plan completion rate deviation as multiple objective functions.
Further, the objective functions of minimizing new energy power-off cost, day-ahead output plan adjustment cost, day-ahead power plan deviation cost and day-ahead power plan completion rate deviation are as follows:
Figure BDA0003083114950000031
wherein f 1 ～f 4 Is a 4-project label function; f (f) 4 、f 2 、f 3 And f 4 Sequentially minimizing new energy power-off cost, day-ahead output plan adjustment cost, day-ahead electric quantity plan deviation cost and day-ahead electric quantity plan completion rate deviation objective functions; t is t 0 Is the current moment; t is the end time of the day; Δt is the rolling schedule time interval; n (N) RE The system is a new energy power plant number, and comprises a wind power plant and a photovoltaic power plant;
Figure BDA0003083114950000032
the electricity discarding cost of the new energy power plant i; />
Figure BDA0003083114950000033
The electric power is discarded by the new energy power plant i at the time t; n (N) Hydro Is the number of hydropower plants; />
Figure BDA0003083114950000034
Is the electricity discarding cost of the hydropower plant i; />
Figure BDA0003083114950000035
Is the abandoned electricity quantity of the hydropower plant i; n (N) Thermal Is the number of thermal power plants; />
Figure BDA0003083114950000036
Is the number of units of the power plant i; k is the type of output adjustment; />
Figure BDA0003083114950000037
The method is characterized in that the adjustment cost of the upward adjustment quantity and the adjustment cost of the downward adjustment quantity of the output of a unit of the thermal power plant i in a k interval are respectively; />
Figure BDA0003083114950000038
Is the adjustment quantity of a unit j of the thermal power plant i in a k section at the moment t; />
Figure BDA0003083114950000039
The unit output up-regulation quantity adjustment cost and the unit output down-regulation quantity adjustment cost of the non-thermal power plant i respectively;
Figure BDA00030831149500000310
the output adjustment quantity of the non-thermal power plant i at the time t; n is the number of all power plants; n (N) contract Is the number of medium-and-long-term contract types signed by the power plant; />
Figure BDA0003083114950000041
Is the deviation electricity quantity of the power generation quantity of the contract c in the day-ahead plan of the power plant i; />
Figure BDA0003083114950000042
Is the electricity deviation cost of the power plant i contract c; />
Figure BDA0003083114950000043
Is the deviation electricity quantity of the power generation quantity outside the contract in the day-ahead plan of the power plant i; />
Figure BDA0003083114950000044
The deviation cost of the power generation amount outside the contract of the power plant i; />
Figure BDA0003083114950000045
The daily power generation amount of the power plant i is increased; />
Figure BDA0003083114950000046
The power generation cost is increased in the day i of the power plant; n (N) type Is the number of power supply types; />
Figure BDA0003083114950000047
Is the deviation value of the power generation completion rate of the daily planned contract c of the power plant i; />
Figure BDA0003083114950000048
Is the deviation value of the completion rate of the power generation capacity outside the planned contract before the power plant i days.
Further, the multi-objective optimization of the objective function is converted into single-objective optimization, and the process is as follows:
Figure BDA0003083114950000049
in the method, in the process of the invention,
Figure BDA00030831149500000410
respectively the weight factors corresponding to the g target positive deviation and the g target negative deviation; />
Figure BDA00030831149500000411
Positive and negative deviations of the objective function g from the target value, respectively; f (f) g A function g that is a target constraint; />
Figure BDA00030831149500000412
As a target value of a function g, f g Optimal values for single-objective optimization of the objective function.
Further, the daily optimization scheduling model considering electric quantity coordination meets the power supply operation constraint, and the method specifically comprises the following steps:
force constraint:
Figure BDA00030831149500000413
Figure BDA00030831149500000414
wherein P is i,j,t The unit j of the power plant i is subjected to rolling correction and then the unit output at the time t; u (u) i,j,t The starting state of a unit j of a power plant i at a moment t in daily rolling optimization is set; p (P) i,j,max ,P i,j,min The maximum and minimum technical output of the unit j in the power plant i are respectively; RE is a new energy power plant type comprising wind power and photovoltaic;
Figure BDA00030831149500000415
the output of the new energy power plant i at the time t after rolling correction; />
Figure BDA00030831149500000416
The predicted force value of the new energy power plant i at the time t is obtained;
and (3) unit climbing constraint:
Figure BDA00030831149500000417
in the method, in the process of the invention,
Figure BDA0003083114950000051
the upward climbing rate and the downward climbing rate of the unit j in the power plant i are respectively.
Further, the daily optimization scheduling model considering electric quantity coordination meets the system operation constraint, and specifically comprises the following steps:
power balance constraint:
Figure BDA0003083114950000052
wherein D is t Is the system load at time t;
network security constraints:
Figure BDA0003083114950000053
direct current power flow modeling is adopted, wherein P is l,min ,P l,max The active power flow limits of line l, respectively; g l,i The generator transfer distribution factor of the unit to the line I; d (D) j,t Is the load at time t of node j;
system standby constraints:
Figure BDA0003083114950000054
in sr t ,sd t The minimum upper rotational reserve and minimum lower rotational reserve capacity of the system at time t, respectively.
Further, the intra-day optimization scheduling model considering electric quantity coordination meets the coupling constraint with the day-ahead plan, and is specifically as follows: the output state of the thermal power generating unit is divided into three load states of obligation peak shaving and first gear peak shaving and second gear peak shaving according to the requirements of a peak shaving auxiliary service market, and peak shaving with the output of more than 50% is obligation peak shaving; peak shaving with output lower than 50% and higher than 40% is first gear peak shaving; peak shaving when the output is lower than 40% is second gear peak shaving; dividing the difference value part between the daily output and the daily planned output of the thermal power generating unit into 3 adjustment amounts in intervals according to three peak regulation states;
Figure BDA0003083114950000055
in the method, in the process of the invention,
Figure BDA0003083114950000056
the output of a unit j of a power plant i at a time t in a day-ahead plan; />
Figure BDA0003083114950000057
The up-regulating and down-regulating output of a unit j of the power plant i at the time t are respectively; />
Figure BDA0003083114950000058
Respectively the adjustment quantity of a unit j of the power plant i in an obligation peak regulation interval at the moment t; />
Figure BDA0003083114950000059
The adjustment amounts of the unit j of the power plant i in the first gear peak regulation interval at the moment t are respectively;
Figure BDA00030831149500000510
respectively the adjustment quantity of a unit j of the power plant i in a second gear peak regulation interval at the moment t;
output coupling constraint of hydroelectric generating set:
Figure BDA0003083114950000061
output coupling constraint of new energy unit: />
Figure BDA0003083114950000062
In the method, in the process of the invention,
Figure BDA0003083114950000063
the output of the new energy power plant i at the moment t in the day-ahead plan is obtained.
Further, the daily optimization scheduling model considering electric quantity coordination meets the daily electric quantity execution coordination constraint, and specifically comprises the following steps:
setting power plant to share N Contract Seed contracts, sequence number 1 to N Contract The priority is decreased;
Figure BDA0003083114950000064
Figure BDA0003083114950000065
Figure BDA0003083114950000066
Figure BDA0003083114950000067
/>
wherein E is i The total daily power generation amount of the power plant i comprises the power generation amount of the current running period and the power generation amount of the follow-up adjustment plan; Δt is the scroll time step;
Figure BDA0003083114950000068
is the power plant i at t 0 The actual running power at a certain time t before the moment; e (E) i,c Is the power generation of contract c of power plant i on the same day; η (eta) i,c Is the ratio of the generated energy of the contract c of the power plant i to the generated energy of the contract c before the day; />
Figure BDA0003083114950000069
Is power plant i contract cPlanning the generating capacity before the day; η (eta) i,extra Is a linearization parameter of the power generation capacity outside the contract of the power plant i; />
Figure BDA00030831149500000610
Is the power generation capacity of the power plant i except the contract power in the day; />
Figure BDA00030831149500000611
The power generation capacity of the power plant i outside the contract electric quantity in the day-ahead plan; />
Figure BDA00030831149500000612
The power plant i adds new electric quantity in the day of the day; />
Figure BDA00030831149500000613
Is the contracted external electric quantity deviation of the power plant i before the day; lambda (lambda) i,c ,λ i,extra Is an auxiliary parameter of 0-1;
contract power completion rate coordination constraints:
Figure BDA0003083114950000071
Figure BDA0003083114950000072
Figure BDA0003083114950000073
in the method, in the process of the invention,
Figure BDA0003083114950000074
the auxiliary parameter is 0-1, the variable is 1 when the power plant i has the power generation capacity of the c-type contract in the day-ahead plan, and otherwise, the variable is 0; />
Figure BDA0003083114950000075
Positive and negative deviations of the contract electrical quantity completion rate, respectively; />
Figure BDA0003083114950000076
The execution rate of the contract electric quantity of c is arranged in the future of the whole type power plant; />
Figure BDA0003083114950000077
Is an auxiliary parameter of 0-1, if the power plant exists in the power type and has the contract power generation capacity of type c in the plan before the day, the variable is 1, otherwise, the variable is 0;
out-of-contract power generation completion rate coordination constraint:
Figure BDA0003083114950000078
Figure BDA0003083114950000079
Figure BDA00030831149500000710
in the method, in the process of the invention,
Figure BDA00030831149500000711
is an auxiliary parameter of 0-1, if the power plant has an extra-contract power generation capacity in the project before i days, the variable is 1, otherwise, the variable is 0; η (eta) i,f The execution rate of the power generation capacity outside the contract before the day of the power plant i; />
Figure BDA00030831149500000712
Positive deviation and negative deviation of the power generation completion rate outside the contract are respectively; />
Figure BDA00030831149500000713
The contract outer generating capacity execution rate of the type power plant; />
Figure BDA00030831149500000714
Is an auxiliary parameter of 0-1, and the power plant in the power type has the extracontractual power generation capacity in the day-ahead planThe variable is 1 and otherwise 0.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, the effectiveness and fairness of the daily power schedule of the unit during daily operation are described in a quantized form through modeling the daily power schedule, the power schedule adjustment quantity and the power completion progress; the daily dispatching decision of the electric power system is obtained after the comprehensive economy, dispatching fairness and new energy consumption are optimal, the requirement of 'three-metric' dispatching in the electric power market transition period is met, and the problem that the daily electric power control is suitable for the change of the power grid operation environment is solved.
Drawings
Fig. 1 is a flowchart of a daily rolling scheduling method considering electric quantity coordination according to the present invention.
FIG. 2 is a graph showing the results of scheduling power during and before each power plant day.
FIG. 3 is a graph of the power planning completion fairness results for each power plant.
Detailed Description
The present invention will be described in detail with reference to the accompanying drawings.
Referring to fig. 1-3, a daily rolling optimization scheduling method considering electric quantity coordination is introduced into a target planning method, the maximum new energy consumption, the tracking of a daily output plan, the tracking of a daily electric quantity plan containing contract decomposed electric quantity and the minimum deviation of the completion rate of each power plant electric quantity plan are taken as multiple targets, the real-time acquired unit state information, new energy prediction output information and daily planned electric quantity completion condition are comprehensively considered, a daily optimization scheduling model is dynamically rolled, the start-stop mode of a daily unit and the active scheduling value of each time unit are determined, the requirement of 'three-public scheduling' is met under the transition period of an electric power market, and the effective and fair execution of the daily electric quantity plan is considered.
Referring to fig. 1, the present invention specifically includes the steps of:
step one, acquiring a day-ahead dispatching plan of the power system as input, wherein the day-ahead dispatching plan comprises a set start-stop, output information and an electric quantity plan. The power schedule comprises daily total power generation capacity of each power plant and contract power generation capacity, wherein the daily total power generation capacity and the contract power generation capacity are arranged in a daily scheduling schedule. Here, consider that each power plant signs a certain amount of medium-and-long-term contracts, and the contract electricity quantity is decomposed into executable daily electricity quantity, and a daily schedule plan containing contract electricity generation is obtained after daily schedule.
And step two, updating new energy output power prediction and load prediction information. Dividing 24 hours in a running day into 96 points at 15min intervals, and for a certain running time t in the day 0 Updating the current running time t 0 The state and the actual output of the machine set; for the operating time t 0 And updating the short-term power prediction and the load prediction of the new energy source in the interval from the ending time T of the current day.
Step three, based on the day-ahead dispatching plan of the electric power system obtained in the step one and the updated new energy output power prediction and load prediction information obtained in the step two, taking the maximum new energy consumption, the minimum power generation plan adjustment cost, the minimum electric quantity plan adjustment cost and the minimum electric quantity completion rate deviation in the remaining period of the day as targets, comprehensively considering the power supply constraint, the system operation constraint, the coupling constraint with the day-ahead plan and the daily electric quantity execution coordination constraint, establishing and solving a day-ahead optimized dispatching model considering electric quantity coordination, and adjusting the dispatching period t according to the real-time execution condition of the day-ahead electric quantity plan on the day 0 And the electric quantity completion progress at the end time T of the day is reached, so that an intra-day scheduling scheme with optimal economical efficiency, maximum new energy consumption and balanced electric quantity execution in the remaining target time period of the day is obtained, and the adaptability and execution precision of the intra-day electric quantity plan of the unit to the change of the power grid operation environment are improved.
The daily optimization scheduling model considering electric quantity coordination is constructed through the following processes:
the power coordination day-to-day optimization scheduling model is considered to minimize new energy power rejection cost, day-to-day output plan adjustment cost, day-to-day power plan deviation cost and day-to-day power plan completion rate deviation as multiple objective functions.
Figure BDA0003083114950000091
Wherein f 1 ～f 4 Is a 4-project label function; f (f) 4 、f 2 、f 3 And f 4 Sequentially minimizing new energy power-off cost, day-ahead output plan adjustment cost, day-ahead electric quantity plan deviation cost and day-ahead electric quantity plan completion rate deviation objective functions; t is t 0 Is the current moment; t is the end time of the day; Δt is the rolling schedule time interval; n (N) RE The system is a new energy power plant number, and comprises a wind power plant and a photovoltaic power plant;
Figure BDA0003083114950000092
the electricity discarding cost of the new energy power plant i; />
Figure BDA0003083114950000093
The electric power is discarded by the new energy power plant i at the time t; n (N) Hydro Is the number of hydropower plants; />
Figure BDA0003083114950000101
Is the electricity discarding cost of the hydropower plant i; />
Figure BDA0003083114950000102
Is the abandoned electricity quantity of the hydropower plant i; n (N) Thermal Is the number of thermal power plants; />
Figure BDA0003083114950000103
Is the number of units of the power plant i; considering that the thermal power participates in the deep peak shaving service, the output adjustment quantity of the thermal power is subdivided, k is the output adjustment quantity type, and 0,1 and 2 correspond to obligation, first gear peak shaving and second gear peak shaving respectively; />
Figure BDA0003083114950000104
The method is characterized in that the adjustment cost of the upward adjustment quantity and the adjustment cost of the downward adjustment quantity of the output of a unit of the thermal power plant i in a k interval are respectively; />
Figure BDA0003083114950000105
Is fire of fireThe adjustment quantity of a unit j of a power plant i in a k section at a time t; />
Figure BDA0003083114950000106
The unit output up-regulation quantity adjustment cost and the unit output down-regulation quantity adjustment cost of the non-thermal power plant i respectively; />
Figure BDA0003083114950000107
The output adjustment quantity of the non-thermal power plant i at the time t; n is the number of all power plants; n (N) contract Is the number of medium-and-long-term contract types signed by the power plant; />
Figure BDA0003083114950000108
Is the deviation electricity quantity of the power generation quantity of the contract c in the day-ahead plan of the power plant i; />
Figure BDA0003083114950000109
Is the electricity deviation cost of the power plant i contract c; />
Figure BDA00030831149500001010
Is the deviation electricity quantity of the power generation quantity outside the contract in the day-ahead plan of the power plant i; />
Figure BDA00030831149500001011
The deviation cost of the power generation amount outside the contract of the power plant i; />
Figure BDA00030831149500001012
The daily power generation amount of the power plant i is increased; />
Figure BDA00030831149500001013
The power generation cost is increased in the day i of the power plant; n (N) type Is the number of power supply types; />
Figure BDA00030831149500001014
Is the deviation value of the power generation completion rate of the daily planned contract c of the power plant i;
Figure BDA00030831149500001015
is a day meter of a power plant iAnd dividing the deviation value of the completion rate of the power generation outside the contract.
The daily optimization scheduling model taking the electric quantity coordination into consideration simultaneously considers a plurality of mutually conflicting objective functions, so that an objective planning method is introduced, the distance between each objective function and the objective value of each objective function is shortened as much as possible, and the multi-objective optimization of the objective function is converted into single-objective optimization:
Figure BDA00030831149500001016
in the method, in the process of the invention,
Figure BDA00030831149500001017
respectively the weight factors corresponding to the g target positive deviation and the g target negative deviation; />
Figure BDA00030831149500001018
Positive and negative deviations of the objective function g from the target value, respectively; f (f) g A function g that is a target constraint; />
Figure BDA00030831149500001019
As the target value of the function g, f is generally taken g Optimal values for single-objective optimization of the objective function.
The intra-day optimization scheduling model considering electric quantity coordination satisfies the following constraint:
1. power supply operation constraints
Force constraint:
Figure BDA0003083114950000111
Figure BDA0003083114950000112
wherein P is i,j,t The unit j of the power plant i is subjected to rolling correction and then the unit output at the time t; u (u) i,j,t The starting state of a unit j of a power plant i at a moment t in daily rolling optimization is set;P i,j,max ,P i,j,min the maximum and minimum technical output of the unit j in the power plant i are respectively; RE is a new energy power plant type comprising wind power and photovoltaic;
Figure BDA0003083114950000113
the output of the new energy power plant i at the time t after rolling correction; />
Figure BDA0003083114950000114
The predicted force value of the new energy power plant i at the time t is obtained.
And (3) unit climbing constraint:
Figure BDA0003083114950000115
in the method, in the process of the invention,
Figure BDA0003083114950000116
the upward climbing rate and the downward climbing rate of the unit j in the power plant i are respectively.
2. System operation constraints
Power balance constraint:
Figure BDA0003083114950000117
wherein D is t Is the system load at time t.
Network security constraints:
Figure BDA0003083114950000118
direct current power flow modeling is adopted, wherein P is l,min ,P l,max The active power flow limits of line l, respectively; g l,i The generator transfer distribution factor of the unit to the line I; d (D) j,t Is the load at time t of node j.
System standby constraints:
Figure BDA0003083114950000119
in sr t ,sd t The minimum upper rotational reserve and minimum lower rotational reserve capacity of the system at time t, respectively.
3. Coupling constraints with day-ahead plans
Here mainly the coupling of the intra-day power plan with the pre-day power plan. First, a thermal power generating unit is introduced: the output state of the thermal power generating unit can be divided into three load states of obligation peak shaving and first gear peak shaving and second gear peak shaving according to the requirements of a peak shaving auxiliary service market, and the load states are generally defined according to load rates: peak shaving with the output of more than 50 percent is obligatory peak shaving; peak shaving with output lower than 50% and higher than 40% is first gear peak shaving; peak shaving at an output below 40% is second gear peak shaving. Therefore, the difference part between the daily output and the daily planned output of the thermal power generating unit, namely the adjustment quantity, is divided into adjustment quantities in 3 intervals according to three peak regulation states.
Figure BDA0003083114950000121
In the method, in the process of the invention,
Figure BDA0003083114950000122
the output of a unit j of a power plant i at a time t in a day-ahead plan; />
Figure BDA0003083114950000123
The up-regulating and down-regulating output of a unit j of the power plant i at the time t are respectively; />
Figure BDA0003083114950000124
Respectively the adjustment quantity of a unit j of the power plant i in an obligation peak regulation interval at the moment t; />
Figure BDA0003083114950000125
The adjustment amounts of the unit j of the power plant i in the first gear peak regulation interval at the moment t are respectively;
Figure BDA0003083114950000126
respectively the adjustment amounts of the unit j of the power plant i in the second gear peak regulation interval at the moment t, and all the adjustment amounts are non-negativeA variable.
The output coupling constraint of the hydroelectric generating set and the new energy generating set does not subdivide the adjustment quantity of the output of the generating set. Output coupling constraint of hydroelectric generating set:
Figure BDA0003083114950000127
output coupling constraint of new energy unit: />
Figure BDA0003083114950000128
In (1) the->
Figure BDA0003083114950000129
The output of the new energy power plant i at the moment t in the day-ahead plan is obtained.
4. Solar power execution coordination constraints
The daily electricity quantity execution coordination should ensure that the tracking is finished with the daily electricity quantity plan first. Three types of electricity are contained in the daily electricity generation schedule: the day-ahead contract power generation amount, and the day-ahead plan power generation amount. The concept of piecewise linearization is adopted for constraint, so that the electric quantity after the rolling in the day is coupled with the planned electric quantity before the day, and the order of contract priority is ensured to be followed when the electric quantity in the day is executed.
Setting power plant to share N Contract Seed contracts, sequence number 1 to N Contract The priority is decremented.
Figure BDA00030831149500001210
Figure BDA0003083114950000131
Figure BDA0003083114950000132
Figure BDA0003083114950000133
Wherein E is i The total daily power generation amount of the power plant i comprises the power generation amount of the current running period and the power generation amount of the follow-up adjustment plan; Δt is the scroll time step;
Figure BDA0003083114950000134
is the power plant i at t 0 The actual running power at a certain time t before the moment; e (E) i,c Is the power generation of contract c of power plant i on the same day; η (eta) i,c Is the ratio of the generated energy of the contract c of the power plant i to the generated energy of the contract c before the day; />
Figure BDA0003083114950000135
The planned daily power generation of the power plant i contract c; η (eta) i,extra Is a linearization parameter of the power generation capacity outside the contract of the power plant i; />
Figure BDA0003083114950000136
Is the power generation capacity of the power plant i except the contract power in the day; />
Figure BDA0003083114950000137
The power generation capacity of the power plant i outside the contract electric quantity in the day-ahead plan; />
Figure BDA0003083114950000138
The power plant i adds new electric quantity in the day of the day; />
Figure BDA0003083114950000139
Is the contracted external electric quantity deviation of the power plant i before the day; lambda (lambda) i,c ,λ i,extra Is a 0-1 auxiliary parameter.
On the basis of completing the day-ahead power planning, the power completion rates of the power plants are converged, including a day-ahead contract power completion rate and a day-ahead contract external power completion rate.
Contract power completion rate coordination constraints:
Figure BDA00030831149500001310
Figure BDA00030831149500001311
Figure BDA00030831149500001312
in the method, in the process of the invention,
Figure BDA00030831149500001313
the auxiliary parameter is 0-1, the variable is 1 when the power plant i has the power generation capacity of the c-type contract in the day-ahead plan, and otherwise, the variable is 0; />
Figure BDA0003083114950000141
Positive and negative deviations of the contract electrical quantity completion rate, respectively; />
Figure BDA0003083114950000142
The execution rate of the contract electric quantity of c is arranged in the future of the whole type power plant; />
Figure BDA0003083114950000143
Is an auxiliary parameter of 0-1, and if the power plant exists in the power type and has a contract power generation amount of type c in the future plan, the variable is 1, otherwise, the variable is 0.
Out-of-contract power generation completion rate coordination constraint:
Figure BDA0003083114950000144
Figure BDA0003083114950000145
Figure BDA0003083114950000146
in the method, in the process of the invention,
Figure BDA0003083114950000147
is an auxiliary parameter of 0-1, if the power plant has an extra-contract power generation capacity in the project before i days, the variable is 1, otherwise, the variable is 0; η (eta) i , f The execution rate of the power generation capacity outside the contract before the day of the power plant i; />
Figure BDA0003083114950000148
Positive deviation and negative deviation of the power generation completion rate outside the contract are respectively; />
Figure BDA0003083114950000149
The contract outer generating capacity execution rate of the type power plant; />
Figure BDA00030831149500001410
Is an auxiliary parameter of 0-1, and if the power plant exists in the power type and has an extracontractual power generation capacity in the future plan, the variable is 1, otherwise, the variable is 0.
The variables to be solved of the daily optimization scheduling model considering electric quantity coordination are { u } corresponding to each unit at each moment in the operation day i,j , t ,p i,j , t }. The scheduling model is essentially a mixed integer linear programming model, and a variable solving result is obtained after a branch-and-bound method or a cut plane algorithm is adopted for solving, wherein u i,j , t The unit start-stop plan in the corrected day is corresponding; p is p i,j , t And corresponding to each unit active scheduling value which considers the power planning and the balanced execution.
Step four, taking a unit start-stop and output scheme of the first time period in the remaining time period scheduling scheme determined in the step three as the current time t 0 Is a modification of the above.
Step five, according to the current time t 0 If not, then entering the next moment, namely let t 0 ＝t 0 +1, repeating the second to fifth steps; if so, the whole day rolling scheduling of the day is completed, and an intra-day scheduling plan considering electric quantity coordination is obtained. The intra-day scheduling scheme is used in power system operation,the method can effectively track the daily electric quantity plan, ensure the effectiveness and fairness of electric quantity completion, simultaneously enable all power plants to participate in new energy consumption, and reduce the influence of new energy output fluctuation on system operation.
Taking an actual power system of a certain province in northwest of China as an example, rolling scheduling is carried out all day long, and the power scheduling result of each power plant (11-20 are photovoltaic power plants; 21-26 are wind power plants; 26-31 are thermal power plants) is shown in figure 2. 100% execution of the daily contract electric quantity can be realized by all power plants on the same day, the completion rate deviation of the daily contract electric quantity of the power plants is controlled within the range of 4 percentage points, the daily electric quantity of each power plant is planned to be effectively completed, the planned electric quantity completion rate of each power plant on the same day is basically at the same level, the average value of the contract electric quantity completion rate deviation is 2.76 percentage points as shown in fig. 3, the coordination of the execution of various electric quantities is fully ensured, and the daily electric quantity is planned to be effectively and fairly executed.
The invention introduces a target planning method, takes the maximum new energy consumption, the tracking of the day-ahead power plan including the contract decomposed power and the minimum deviation of the power plan completion rate as multiple targets, comprehensively considers the power grid, the unit state information, the new energy prediction power information and the day-ahead power completion condition acquired in real time, dynamically scrolls the day-ahead optimal scheduling model, so that the power generation plan after the rolling correction realizes the balanced control of the completion progress of the unit day-ahead power plan while improving the new energy consumption, solves the problems that the power control in the unit day-ahead power plan is difficult to adapt to the power grid operation environment change and the manual intervention dependency is high, and ensures the power plant day-ahead power plan to be effectively and fairly executed.

Claims (3)

1. The daily rolling scheduling method considering electric quantity coordination is characterized by comprising the following steps of:
step one, acquiring a power system day-ahead dispatching plan, wherein the power system day-ahead dispatching plan comprises unit start-stop and output information and an electric quantity plan which are arranged day-ahead; the electric quantity plan comprises the daily total power generation amount and the contract power generation amount of each power plant arranged in the daily scheduling plan;
step two, updating ultra-short-term new energy output power prediction and load prediction information;
step three, based on the results obtained in the step one and the step two, establishing and solving a daily optimization scheduling model considering electric quantity coordination, and rolling an electric quantity plan of a correction scheduling period to obtain a daily scheduling scheme considering electric quantity coordination in the remaining period of the day;
taking a unit start-stop and output scheme of a first time period in an intra-day scheduling scheme taking the electric quantity coordination into consideration in the remaining time period of the day as a correction scheme of the current time;
step five, judging whether 96 points are finished or not in the whole day according to the correction scheme, if not, entering the next moment, and repeating the step two to the step five; if the power supply is finished, the whole-day rolling scheduling of the day is finished, an intra-day scheduling plan considering the power coordination is obtained, the effective tracking of the power supply plan before the day is finished according to the intra-day scheduling plan considering the power coordination, and the effectiveness and fairness of the power supply completion are ensured;
in the third step, an intra-day optimization scheduling model considering electric quantity coordination is established through the following processes:
taking an intra-day optimization scheduling model of electric quantity coordination into consideration to minimize new energy electricity discarding cost, day-ahead output plan adjustment cost, day-ahead electric quantity plan deviation cost and day-ahead electric quantity plan completion rate deviation as multiple objective functions;
the objective functions of minimizing new energy power-off cost, day-ahead output plan adjustment cost, day-ahead electric quantity plan deviation cost and day-ahead electric quantity plan completion rate deviation are as follows:
Figure FDA0004137003260000021
wherein f 1 ～f 4 Is a 4-project label function; f (f) 1 、f 2 、f 3 And f 4 Sequentially minimizing new energy power-off cost, day-ahead output plan adjustment cost, day-ahead electric quantity plan deviation cost and day-ahead electric quantity plan completion rate deviation objective functions; t is t 0 Is the current moment; t is the end time of the dayThe method comprises the steps of carrying out a first treatment on the surface of the Δt is the rolling schedule time interval; n (N) RE The system is a new energy power plant number, and comprises a wind power plant and a photovoltaic power plant;
Figure FDA0004137003260000022
the electricity discarding cost of the new energy power plant i; />
Figure FDA0004137003260000023
The electric power is discarded by the new energy power plant i at the time t; n (N) Hydro Is the number of hydropower plants; />
Figure FDA0004137003260000024
Is the electricity discarding cost of the hydropower plant i; />
Figure FDA0004137003260000025
Is the abandoned electricity quantity of the hydropower plant i; n (N) Thermal Is the number of thermal power plants;
Figure FDA0004137003260000026
is the number of units of the power plant i; k is the type of output adjustment; />
Figure FDA0004137003260000027
The method is characterized in that the adjustment cost of the upward adjustment quantity and the adjustment cost of the downward adjustment quantity of the output of a unit of the thermal power plant i in a k interval are respectively; />
Figure FDA0004137003260000028
Is the adjustment quantity of a unit j of the thermal power plant i in a k section at the moment t; />
Figure FDA0004137003260000029
The unit output up-regulation quantity adjustment cost and the unit output down-regulation quantity adjustment cost of the non-thermal power plant i respectively; />
Figure FDA00041370032600000210
The output adjustment quantity of the non-thermal power plant i at the time t; n is the number of all power plants; n (N) contract Is the number of medium-and-long-term contract types signed by the power plant; />
Figure FDA00041370032600000211
Is the deviation electricity quantity of the power generation quantity of the contract c in the day-ahead plan of the power plant i; />
Figure FDA00041370032600000212
Is the electricity deviation cost of the power plant i contract c; />
Figure FDA00041370032600000213
Is the deviation electricity quantity of the power generation quantity outside the contract in the day-ahead plan of the power plant i; />
Figure FDA00041370032600000214
The deviation cost of the power generation amount outside the contract of the power plant i; />
Figure FDA00041370032600000215
The daily power generation amount of the power plant i is increased; />
Figure FDA00041370032600000216
The power generation cost is increased in the day i of the power plant; n (N) type Is the number of power supply types; />
Figure FDA00041370032600000217
Is the deviation value of the power generation completion rate of the daily planned contract c of the power plant i; />
Figure FDA00041370032600000218
The deviation value of the completion rate of the power generation capacity outside the planned contract before the power plant i days;
converting the multi-objective optimization of the objective function into single-objective optimization, wherein the process is as follows:
Figure FDA0004137003260000031
in the method, in the process of the invention,
Figure FDA0004137003260000032
respectively the weight factors corresponding to the g target positive deviation and the g target negative deviation; />
Figure FDA0004137003260000033
Positive and negative deviations of the objective function g from the target value, respectively; f (f) g A function g that is a target constraint; />
Figure FDA0004137003260000034
As a target value of a function g, f g The optimal value of the objective function is optimized in a single objective way;
the daily optimization scheduling model considering electric quantity coordination meets the power supply operation constraint, and is specifically as follows:
force constraint:
Figure FDA0004137003260000035
Figure FDA0004137003260000036
wherein P is i,j,t The unit j of the power plant i is subjected to rolling correction and then the unit output at the time t; u (u) i,j,t The starting state of a unit j of a power plant i at a moment t in daily rolling optimization is set; p (P) i,j,max ,P i,j,min The maximum and minimum technical output of the unit j in the power plant i are respectively; RE is a new energy power plant type comprising wind power and photovoltaic;
Figure FDA0004137003260000037
the output of the new energy power plant i at the time t after rolling correction; />
Figure FDA0004137003260000038
Is the time t of the new energy power plant iA predicted force value is carved;
and (3) unit climbing constraint:
Figure FDA0004137003260000039
in the method, in the process of the invention,
Figure FDA00041370032600000310
the upward climbing rate and the downward climbing rate of the unit j in the power plant i are respectively;
the daily optimization scheduling model considering electric quantity coordination meets the system operation constraint, and is specifically as follows:
power balance constraint:
Figure FDA00041370032600000311
wherein D is t Is the system load at time t;
network security constraints:
Figure FDA00041370032600000312
direct current power flow modeling is adopted, wherein P is l,min ,P l,max The active power flow limits of line l, respectively; g l,i The generator transfer distribution factor of the unit to the line I; d (D) j,t Is the load at time t of node j;
system standby constraints:
Figure FDA0004137003260000041
in sr t ,sd t The minimum upper rotational reserve and minimum lower rotational reserve capacities of the system at time t, respectively;
the daily optimization scheduling model considering electric quantity coordination meets the coupling constraint with a daily schedule, and is specifically as follows: the output state of the thermal power generating unit is divided into three load states of obligation peak shaving and first gear peak shaving and second gear peak shaving according to the requirements of a peak shaving auxiliary service market, and peak shaving with the output of more than 50% is obligation peak shaving; peak shaving with output lower than 50% and higher than 40% is first gear peak shaving; peak shaving when the output is lower than 40% is second gear peak shaving; dividing the difference value part between the daily output and the daily planned output of the thermal power generating unit into 3 adjustment amounts in intervals according to three peak regulation states;
Figure FDA0004137003260000042
in the method, in the process of the invention,
Figure FDA0004137003260000043
the output of a unit j of a power plant i at a time t in a day-ahead plan; />
Figure FDA0004137003260000044
The up-regulating and down-regulating output of a unit j of the power plant i at the time t are respectively; />
Figure FDA0004137003260000045
Respectively the adjustment quantity of a unit j of the power plant i in an obligation peak regulation interval at the moment t; />
Figure FDA0004137003260000046
The adjustment amounts of the unit j of the power plant i in the first gear peak regulation interval at the moment t are respectively;
Figure FDA0004137003260000047
respectively the adjustment quantity of a unit j of the power plant i in a second gear peak regulation interval at the moment t;
output coupling constraint of hydroelectric generating set:
Figure FDA0004137003260000048
output coupling constraint of new energy unit: />
Figure FDA0004137003260000049
In the method, in the process of the invention,
Figure FDA00041370032600000410
the output of the new energy power plant i at the moment t in the day-ahead plan is obtained.
2. The method for rolling schedule in day in consideration of electric quantity coordination according to claim 1, wherein the second step comprises the following procedures: dividing 24 hours in a running day into 96 points at 15min intervals, and for a certain running time t in the day 0 Updating the current running time t 0 The state and the actual output of the machine set; for the operating time t 0 And updating the short-term power prediction and the load prediction of the new energy source in the interval from the ending time T of the current day.
3. The intra-day rolling scheduling method considering electric quantity coordination according to claim 1, wherein the intra-day optimization scheduling model considering electric quantity coordination satisfies a daily electric quantity execution coordination constraint, specifically comprising the following steps:
setting power plant to share N Contract Seed contracts, sequence number 1 to N Contract The priority is decreased;
Figure FDA0004137003260000051
Figure FDA0004137003260000052
/>
Figure FDA0004137003260000053
Figure FDA0004137003260000054
wherein E is i Is the total daily power generation of the power plant iThe quantity comprises the generated energy of the current running period and the generated energy of a follow-up adjustment plan; Δt is the scroll time step;
Figure FDA0004137003260000055
is the power plant i at t 0 The actual running power at a certain time t before the moment; e (E) i,c Is the power generation of contract c of power plant i on the same day; η (eta) i,c Is the ratio of the generated energy of the contract c of the power plant i to the generated energy of the contract c before the day; />
Figure FDA0004137003260000056
The planned daily power generation of the power plant i contract c; η (eta) i,extra Is a linearization parameter of the power generation capacity outside the contract of the power plant i; />
Figure FDA0004137003260000057
Is the power generation capacity of the power plant i except the contract power in the day; />
Figure FDA0004137003260000058
The power generation capacity of the power plant i outside the contract electric quantity in the day-ahead plan; />
Figure FDA0004137003260000059
The power plant i adds new electric quantity in the day of the day; />
Figure FDA00041370032600000510
Is the contracted external electric quantity deviation of the power plant i before the day; lambda (lambda) i,c ,λ i,extra Is an auxiliary parameter of 0-1;
contract power completion rate coordination constraints:
Figure FDA0004137003260000061
Figure FDA0004137003260000062
Figure FDA0004137003260000063
in the method, in the process of the invention,
Figure FDA0004137003260000064
the auxiliary parameter is 0-1, the variable is 1 when the power plant i has the power generation capacity of the c-type contract in the day-ahead plan, and otherwise, the variable is 0; />
Figure FDA0004137003260000065
Positive and negative deviations of the contract electrical quantity completion rate, respectively; />
Figure FDA0004137003260000066
The execution rate of the contract electric quantity of c is arranged in the future of the whole type power plant; />
Figure FDA0004137003260000067
Is an auxiliary parameter of 0-1, if the power plant exists in the power type and has the contract power generation capacity of type c in the plan before the day, the variable is 1, otherwise, the variable is 0;
out-of-contract power generation completion rate coordination constraint:
Figure FDA0004137003260000068
/>
Figure FDA0004137003260000069
Figure FDA00041370032600000610
in the method, in the process of the invention,
Figure FDA00041370032600000611
is an auxiliary parameter of 0-1, if the power plant has an extra-contract power generation capacity in the project before i days, the variable is 1, otherwise, the variable is 0; η (eta) i,f The execution rate of the power generation capacity outside the contract before the day of the power plant i; />
Figure FDA00041370032600000612
Positive deviation and negative deviation of the power generation completion rate outside the contract are respectively; />
Figure FDA00041370032600000613
The contract outer generating capacity execution rate of the type power plant; />
Figure FDA00041370032600000614
Is an auxiliary parameter of 0-1, and if the power plant exists in the power type and has an extracontractual power generation capacity in the future plan, the variable is 1, otherwise, the variable is 0./>
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