CN112398176A - Day-ahead optimized scheduling method of water-fire-wind mutual aid system considering start-stop peak regulation of coal-fired unit - Google Patents
Day-ahead optimized scheduling method of water-fire-wind mutual aid system considering start-stop peak regulation of coal-fired unit Download PDFInfo
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Abstract
The invention discloses a day-ahead optimization scheduling method of a water-fire-wind mutual aid system considering the start-stop peak regulation of a coal-fired unit. Meanwhile, the method has the technical advantages of wide application range and low realization difficulty, and has obvious effect on improving the consumption capability of clean energy in China.
Description
Technical Field
The invention relates to the technical field of power dispatching, in particular to a day-ahead optimized dispatching method of a water-fire-wind mutual aid system considering the start-stop peak shaving of a coal-fired unit.
Background
In recent years, power system dispatching operation faces increasingly severe peak regulation pressure, on one hand, social and economic development and residential and commercial power utilization increase to cause increase of power utilization peak-valley difference, on the other hand, new energy such as wind power and the like are rapidly developed, and the inverse peak regulation characteristic is obvious. The method for optimizing the day-ahead scheduling plan of the power grid in a fine consideration of the peak shaving capacity of the power grid becomes a research key point.
Different types of power supplies have different peak shaving capabilities. In summary, new energy sources such as wind power and photovoltaic generally do not have peak shaving capability; the cascade hydroelectric power can be stopped and peak-shaving under the requirement of no water-abandoning risk; thermal power generally only provides basic peak regulation auxiliary service, and can also provide two types of paid peak regulation auxiliary service of deep peak regulation and start-stop peak regulation according to system requirements. The current research on the day-ahead scheduling optimization method of the power grid considering the peak shaving capability mainly focuses on the field of deep peak shaving of coal-fired units.
However, no research result of day-ahead optimization scheduling method considering start-stop peak shaving exists at present. In fact, from the practical application situation in recent years, the existing power supply deep peak shaving auxiliary service is difficult to meet the system operation requirement, and considering start-stop peak shaving in the day-ahead optimal scheduling link becomes an inevitable requirement for research in the optimal scheduling field. Compared with the day-ahead optimization scheduling only considering deep peak shaving, the method has the difficulties that the start and stop of the coal-fired unit mathematically belongs to the planning problem containing mixed integers, the output curve in the starting or stopping process is generally a fixed start and stop curve, direct modeling is difficult, and the complexity of refined solution is higher.
Disclosure of Invention
In view of the above, the present invention provides a day-ahead optimized scheduling method for a water-fire-wind mutual aid system considering the start-stop peak shaving of a coal-fired unit, which can solve the problems proposed in the background art.
The purpose of the invention is realized by the following technical scheme:
a day-ahead optimized scheduling method of a water-fire-wind mutual aid system considering start-stop peak shaving of a coal-fired unit comprises the following steps:
step S1: day-ahead optimal scheduling without consideration of coal-fired unit peak shaving
The peak regulation demand distribution factor index is introduced into an optimization target to realize the maximization of the whole network operation benefit after the peak regulation influence is considered, the peak regulation demand distribution factor optimization target comprises two parts, the first part is the maximum peak regulation demand minimum to avoid starting and stopping peak regulation as far as possible, and the second part is the minimum total amount of the regulation demand to reduce the peak regulation cost;
step S2: peak shaver demand statistics
According to the solving result of the step S1, the peak shaving requirements of the system in each time period are statistically analyzed, and an optimal scheduling scheme which meets the lowest total power grid electricity purchasing cost and has the most reasonable peak shaving requirement distribution factor can be obtained through the step S1, wherein the optimal result is the peak shaving requirements in each time period;
step S3: start-stop peak shaving demand determination
The implementation purpose of the step is to judge whether the start and stop of the unit need to be arranged according to the full-network deep peak regulation capacity;
step S4: coal-fired unit capable of determining start-stop peak shaving
Optimizing and compiling the start-stop peak regulation of the coal-fired unit according to the full-network start-stop peak regulation requirement;
step S5: start-stop peak regulation optimization compilation
On the basis of determining starting and stopping of the coal-fired unit, further determining the shutdown period of the coal-fired unit, and making a power generation plan during splitting and grid connection of the coal-fired unit;
step S6: deep peak shaving optimization compilation
Optimally arranging a power generation plan of a coal-fired unit at a deep peak shaving period according to the peak shaving requirement of the whole network;
step S7: generating a power generation plan
And (4) correcting the day-ahead optimization scheduling compilation result formed by the day-ahead optimization scheduling model without considering the peak shaving of the coal-fired unit by considering the deep peak shaving optimization compilation result to obtain the power generation plans of different types of power supplies of the whole network.
Specifically, in step S1, the optimization objective after introducing the peak shaver demand distribution factor includes two parts, which are the total grid electricity purchase cost and the peak shaver demand distribution factor, and can be expressed as:
in the formula (1), NG is the number of units of the whole network, NT is the number of optimized time segments, Delta T is the corresponding time interval, and pg(P) is the declaration price of the unit under different power generation output forces P,
is the planned generated output, P, of the unit at the g time period tt CIs the peak shaver requirement for time period t.
Respectively optimizing the weight coefficients of the target item for the electricity purchasing cost optimization target item and the peak regulation demand distribution factor optimization target item,
the maximum peak shaving demand and the total amount of the adjustment demand in the peak shaving demand distribution factors are respectively.
Specifically, in step S1, the constraint conditions include a power balance constraint, a network transmission constraint, and a unit operating characteristic constraint.
The power balance constraint requires that the generated power in each time interval should be balanced with the load demand, and if the minimum output limit of the unit is exceeded, the generated power is balanced by the reduction amount of the generated power, which can be expressed as:
in the formula (2), NB represents the number of system nodes,
load prediction for a time period t of a node b;
network transmission constraints require that the operating section flow at each time interval does not exceed the transmission limit, which can be expressed as:
in the formula (3), the reaction mixture is,
upper and lower limit values of transmission capability of operation section s, GSDFs,g、GSDFs,bRespectively are power transfer distribution factors of the unit g, the node b and the operation section s;
the unit operation characteristic constraint refers to the self output variation characteristics required to be met by different types of units such as hydropower, thermal power, wind power and the like.
Particularly, in the step S3, because the deep peak shaving cost of the coal-fired unit is much lower than that of the start-stop peak shaving, when the deep peak shaving capability can meet the peak shaving requirement of the power grid, the start-stop peak shaving is not needed; the coal-fired unit deep peak shaving capability is the difference between the minimum technical output and the deep-shaving minimum output, and the full-network deep peak shaving capability is the sum of the deep peak shaving capabilities of all the coal-fired units, and can be expressed as:
in the formula (9), PPAIn order to realize the full-network deep peak regulation capability,
the minimum output force is deeply adjusted for the coal-fired unit g, and g belongs to f and represents all thermal power generating units;
if the full-network depth peak regulation capacity at any time interval is greater than the depth peak regulation demand, the unit start-stop peak regulation is not needed, otherwise, the unit start-stop peak regulation is needed, and the judgment conditions can be expressed as follows:
PPA≥Pt C (10)
if the determination condition in the expression (10) is satisfied in any period, the process proceeds to step S6, otherwise, the process proceeds to step S4.
Specifically, in step S4, the difference between the full-network start-stop peak shaving requirement and the time interval when the full-network deep shaving capability cannot meet the full-network peak shaving requirement may be represented as:
in the formula (11), Pt SNThe full-network start-stop peak regulation requirement is met in a time period t;
considering that the coal-fired unit is converted into the start-stop peak regulation after providing the deep peak regulation, the peak regulation capability which can be increased is the minimum output of the deep peak regulation, and the coal-fired unit which needs to provide the start-stop peak regulation service is the combination of the coal-fired units which can just meet the maximum start-stop peak regulation requirement of the whole network in each period according to the sequence of the sum of the start-stop peak regulation capabilities, and can be expressed as follows:
in the formulas (12) to (13), the sum of the start-stop peak regulation capacities of the front gs-1 coal-fired units is smaller than the maximum start-stop peak regulation requirement of the whole network, and the sum of the start-stop peak regulation capacities of the front gs coal-fired units is larger than the maximum start-stop peak regulation requirement of the whole network, so that the front gs are the start-stop peak regulation units.
In particular, in step S5, in order to reduce the influence of start-stop peak shaving on start-stop peak shaving coal-fired units as much as possible, it is desirable that the shutdown period is as short as possible, and the requirements of start-stop peak shaving technology are met, according to the optimization programming requirements, the start-stop peak shaving optimization programming can be converted into an optimization planning problem, and the optimization target is that the start-stop peak shaving period is as short as possible, and can be expressed as:
in the formula (14), the compound represented by the formula (I),
starting and stopping a coal-fired unit at a g time period t, wherein the starting and stopping state variable takes a value of 1 to indicate that the coal-fired unit is in a shutdown peak shaving state at the moment, and takes a value of 0 to indicate that the moment is in shutdown peak shaving;
the constraint conditions to be considered comprise peak regulation demand constraint, peak regulation state variable relation constraint and start-stop frequency constraint, wherein the peak regulation demand constraint requires that the start-stop peak regulation capacity provided by starting and stopping the coal-fired unit is greater than the start-stop peak regulation demand in each period, the peak regulation state variable relation constraint is used for defining the relation among the start-stop state variable, the start-stop state variable and the stop state variable, and the start-stop frequency constraint requires that the coal-fired unit provides 1 start-stop at most, which can be expressed as:
in the formulae (15) to (17),
starting state variables and stopping state variables of the coal-fired unit at the g time period t are both state variables with the value of 0 or 1, the starting state variable value of 1 indicates that the coal-fired unit is converted from stopping to being connected to the grid at the moment, and the stopping state variable value of 1 indicates that the coal-fired unit is converted from being connected to the grid to stopping at the moment;
and (3) by taking the formula (14) as an optimization target and the formulas (15) to (17) as constraint conditions, constructing a start-stop peak-shaving optimization compilation model and solving the model.
Particularly, according to the solving result of the start-stop peak shaving optimization compilation model, the power generation plan of the start-stop peak shaving coal-fired unit in the stop peak shaving period is 0, 1-2 hours are reserved respectively as the start-stop transition period of the start-stop peak shaving coal-fired unit according to the declared start-stop and stop curves of the start-stop peak shaving coal-fired unit, the coal-fired unit generates power according to the start-stop or stop curves in the transition period, the power generation plan is the start-stop or stop curves, the stop peak shaving period and the transition period power generation plan are taken as boundary conditions to be brought into the step S1, the economic dispatch without considering the deep peak shaving of the coal-fired unit is recalculated, and.
In particular, in step S6, the coal-fired unit should share the demand of the full-grid deep peak shaving according to the equal load rate principle, and considering that different coal-fired units have different deep peak shaving capabilities, the deep peak shaving optimization compilation optimization target is a target of the highest balance of the deep peak shaving amount of the coal-fired unit, and may be expressed as:
in the formula (18), the reaction mixture,
the deep peak regulation capacity C of the coal-fired unit in the g period tgInstalled capacity of coal-fired unit g, CFIs the sum of the capacities of the whole-screen coal burner assembling machine,
indicating the burning of coalThe set of the units which do not participate in starting, stopping and peak regulation in the units;
representing the peak shaving load rate of the coal-fired unit g,
the average peak load regulation rate of the whole network in the time period;
the constraint condition to be considered is peak regulation capacity constraint, and the requirement that the deep peak regulation capacity provided by each coal-fired unit does not exceed the deep regulation minimum output range can be expressed as follows:
and (3) by taking the formula (18) as an optimization target and the formula (19) as a constraint condition, constructing a deep peak regulation optimization compilation model of the coal-fired unit and solving the deep peak regulation optimization compilation model.
Specifically, in step S7, the period-by-period power generation plan of the coal-fired unit should be a part of the day-ahead optimized scheduling output power generation plan minus the deep peak shaving plan without considering peak shaving, which can be expressed as:
in the formula (20), the reaction mixture is,
respectively performing g-time t power generation plans of the coal-fired unit after peak regulation correction and without peak regulation;
the hydropower and wind power generation plan is a day-ahead optimized dispatching output power generation plan without considering peak shaving, namely:
in the formula (21), the compound represented by the formula,
and respectively carrying out time period t power generation plans of the hydroelectric generating set g or the wind power plant g after peak regulation correction and without peak regulation.
The invention has the beneficial effects that:
(1) the optimal scheduling method for solving the problem of finely considering the start-stop peak shaving of the coal-fired unit is provided, and can be used for solving the practical problem of peak shaving optimization in the current scheduling operation field;
(2) the method is characterized in that a modeling solving method of a water-fire-wind complementary system is intensively researched by combining the actual conditions of China, on one hand, water-fire-wind mutual aid is a basic power supply structure of most provinces of China, the solving method constructed aiming at the power supply structure is stronger in pertinence, on the other hand, other types of power supplies such as nuclear power, photovoltaic power, fuel gas and the like are similar to the peak regulation characteristics of the power supplies, and the method can be used for other more complex power grid systems by simplifying or simply expanding, and has wider application range.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the present invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
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In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings, in which:
FIG. 1 is a schematic flow chart of the method of the present invention.
Detailed Description
Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be understood that the preferred embodiments are illustrative of the invention only and are not limiting upon the scope of the invention.
As shown in FIG. 1, the day-ahead optimized scheduling method of the water-fire-wind mutual aid system considering the start-stop peak shaving of the coal-fired unit comprises the following steps:
step S1: day-ahead optimal scheduling without consideration of coal-fired unit peak shaving
The implementation of the step aims to optimally compile a power grid power generation plan on the premise of not considering the starting and stopping of the coal-fired unit and deep peak regulation so as to determine the peak regulation requirement of each time period. It must be pointed out that the current scheduling plan modes of each province in China are different, and the optimization scheduling standards in the day ahead are also different. Without loss of generality, the economic scheduling model with wider application is taken as a sample according to the invention, and the implementation process introduced by the invention is only needed to be correspondingly adjusted in other scheduling modes. The operation cost of the coal-fired unit is obviously changed along with the operation condition, the cost of the non-peak-shaving state is obviously lower than that of the deep peak-shaving state, and the cost of starting and stopping peak shaving is greatly higher than that of the deep peak-shaving state. Therefore, in order to reduce the system operation cost and improve the operation benefit, peak regulation should be avoided as much as possible, and the peak regulation condition of the coal-fired unit should be solved as much as possible through deep peak regulation.
The traditional economic dispatching model only takes the minimum electricity purchasing cost of the whole network as an optimization target. In the invention, in order to realize the connection of day-ahead optimized scheduling and subsequent peak shaving optimization and realize the maximization of the overall scheduling benefit, the peak shaving demand distribution factor index is introduced into the optimization target based on the characteristic rule of the coal-fired unit operation cost so as to realize the maximization of the whole network operation benefit after the peak shaving influence is considered. The peak regulation demand distribution factor optimization target comprises two parts, wherein the first part is the maximum peak regulation demand minimum so as to avoid starting and stopping peak regulation as far as possible, and the second part is the adjustment demand total minimum so as to reduce peak regulation cost. The optimization target after the introduction of the peak regulation demand distribution factor comprises two parts, namely the total grid electricity purchase cost and the peak regulation demand distribution factor, which can be expressed as follows:
in the formula (1), NG is the number of units of the whole network, NT is the number of optimized time segments, Delta T is the corresponding time interval, and pg(P) is the declaration price of the unit under different power generation output forces P,
is the planned generated output, P, of the unit at the g time period tt CIs the peak shaver requirement for time period t.
Respectively optimizing the weight coefficients of the target item for the electricity purchasing cost optimization target item and the peak regulation demand distribution factor optimization target item,
the maximum peak shaving demand and the total amount of the adjustment demand in the peak shaving demand distribution factors are respectively. Wherein the content of the first and second substances,
the upper label, Fee, is the Fee English fe,
in the superscript, peak is peak-peak English peak, NG is the first letter combination of the number of generator sets, NT is the first letter combination of the number of time periods, P (upper case) is the first letter of power English power, P (lower case) is the first letter of price English, g is the first letter of generator sets,
s in the superscript is the first letter of the planned english schedule,
d in the superscript is the first letter of deep english deep,
q in the superscript is the first letter of the number, Pt CC in the superscript is the first letter to Cut down english Cut.
The constraint conditions comprise power balance constraint, network transmission constraint and unit operation characteristic constraint.
The power balance constraint requires that the generated power in each time interval should be balanced with the load demand, and if the minimum output limit of the unit is exceeded, the generated power is balanced by the reduction amount of the generated power, which can be expressed as:
in the formula (2), NB represents the number of system nodes,
load prediction for node b time period t. Wherein NB is the first letter combination of the node number of bus,
f in the superscript is the first letter to predict english forecast.
Network transmission constraints require that the operating section flow at each time interval does not exceed the transmission limit, which can be expressed as:
in the formula (3), the reaction mixture is,
upper and lower limit values of transmission capability of operation section s, GSDFs,g、GSDFs,bThe power transfer distribution factors of the unit g, the node b and the operation section s are respectively. Wherein the content of the first and second substances,
in the superscript, max and min are the first three letters of maximum and minimum English respectively, and GSDF is the initial combination of the power transfer distribution factor English Generation shift distribution factor.
The unit operation characteristic constraint refers to the self output variation characteristics required to be met by different types of units such as hydropower, thermal power, wind power and the like. For the hydroelectric generating set, output range constraint and all-day electric quantity constraint are mainly considered, the output range constraint requires that the generated output of the hydroelectric generating set cannot exceed the maximum technical output, the all-day electric quantity constraint means that in order to meet the requirement of clean energy consumption, the all-day accumulated generated energy is within the range of the generated electric quantity, and can be expressed as:
in the formulae (4) to (5),
the maximum technical output of the hydroelectric generating set g,
the maximum generating capacity and the minimum generating capacity of the hydropower plant h on the day are respectively, and g belongs to h and represents all the hydropower units belonging to the hydropower plant h. Wherein E is the first letter of the electricity English Energy, and h is the first letter of the hydropower English.
For the thermal power generating unit, output range constraint and climbing capacity constraint are mainly considered, the output range constraint requires that the generated output of the thermal power generating unit is within the maximum and minimum technical output ranges, the climbing capacity constraint means that the generated output variation of the unit is within the maximum and minimum climbing capacity limit values during a time period, and can be expressed as follows:
in the formulae (6) to (7),
for maximum and minimum technical output of the thermal power generating unit g, it should be specially noted that,
in order to take into account the minimum technical output during deep peak shaving, if the generated output is lower than
Indicating that the generator set provides deep peak shaving auxiliary service;
the maximum and minimum climbing capacity limit values of the thermal power generating unit g are respectively. Wherein, PC is the first letter combination of power clinmbig in power ramp.
For new energy power stations such as wind power stations and the like, power generation is predicted according to the power generation method in the step, and the power generation method can be expressed as follows:
in the formula (8), the reaction mixture is,
and predicting the generated power of the wind power plant in the period g and t.
And (3) constructing a day-ahead optimization scheduling model without considering the peak shaving of the coal-fired unit by taking the formula (1) as an optimization target and the formulas (2) to (8) as constraint conditions. The solution of the model can be realized by using commercial planning software such as Cplex and the like or a planning algorithm such as an interior point method and the like, and for the technical personnel in the field, no technical obstacle exists, and the specific implementation process is not repeated.
Step S2: peak shaver demand statistics
According to the solving result of the step S1, the peak shaving requirements of the system in each time period are statistically analyzed, and an optimal scheduling scheme which meets the lowest total power grid electricity purchasing cost and has the most reasonable peak shaving requirement distribution factor can be obtained through the step S1, wherein the optimal result is the peak shaving requirements in each time period;
step S3: start-stop peak shaving demand determination
The implementation purpose of the step is to judge whether the start and the stop of the unit need to be arranged according to the full-network deep peak regulation capacity. Because the deep peak regulation cost of the coal-fired unit is far lower than that of starting and stopping peak regulation, the starting and stopping peak regulation can be omitted when the deep peak regulation capability can meet the peak regulation requirement of a power grid. The coal-fired unit deep peak shaving capability is the difference between the minimum technical output and the deep-shaving minimum output, and the full-network deep peak shaving capability is the sum of the deep peak shaving capabilities of all the coal-fired units, and can be expressed as:
in the formula (9), PPAIn order to realize the full-network deep peak regulation capability,
and g belongs to f and represents all thermal power generating units. Wherein, PA is the combination of the first letter of peak ability English, f is the first letter of fire English.
If the full-network depth peak regulation capacity at any time interval is greater than the depth peak regulation demand, the unit start-stop peak regulation is not needed, otherwise, the unit start-stop peak regulation is needed, and the judgment conditions can be expressed as follows:
PPA≥Pt C (10)
if the determination condition in the expression (10) is satisfied in any period, the process proceeds to step S6, otherwise, the process proceeds to step S6.
Step S4: coal-fired unit capable of determining start-stop peak shaving
The implementation of the step aims to optimally compile start-stop peak shaving of the coal-fired unit according to the requirements of the whole network start-stop peak shaving. The aim of starting and stopping peak regulation optimization compilation is to arrange the starting and stopping of the coal-fired unit with the minimum starting and stopping peak regulation cost on the basis of meeting the peak regulation requirement of the whole network. For the areas where the peak shaving auxiliary service market is established, the coal-fired unit start-stop peak shaving quotations can be used for sequencing and carrying out optimization compilation; for the areas where the peak shaving auxiliary service market is not established, the sequencing optimization compilation can be carried out according to the proportion of the coal-fired units in operation by adopting a three-public scheduling principle. Without loss of generality, the implementation process is introduced by taking the establishment of the peak shaving auxiliary service market as an example. According to the fact that the peak-load-adjusting declaration price of the start-stop of the coal-fired units is from small to large and the unit capacity is from small to large, the coal-fired units can be sequenced.
The whole network starts to stop the peak regulation demand for the time interval difference between the whole network deep tone ability can not satisfy the whole network peak regulation demand, can be expressed as:
in the formula (11), Pt SNAnd the peak regulation requirement of starting and stopping the whole network at the time t is met. Wherein, SN is the initial combination of the starting requirement English started need.
The coal-fired unit is converted into start-stop peak regulation after deep peak regulation is provided, and the peak regulation capacity which can be increased is the minimum output of the deep peak regulation. The coal-fired unit which needs to provide the start-stop peak shaving service is a combination of the coal-fired units which can just meet the maximum start-stop peak shaving requirement of the whole network at each time period according to the sequence of the sum of the start-stop peak shaving capabilities of the coal-fired units, and can be represented as follows:
in the formulas (12) to (13), the sum of the start-stop peak regulation capacities of the front gs-1 coal-fired units is smaller than the maximum start-stop peak regulation requirement of the whole network, and the sum of the start-stop peak regulation capacities of the front gs coal-fired units is larger than the maximum start-stop peak regulation requirement of the whole network. The front gs platform is the start-stop peak shaving unit. Wherein g in gs is the first letter of the generator set English generator, and s is the first letter of the starting English start.
Step S5: start-stop peak regulation optimization compilation
The implementation purpose of the step is to further determine the shutdown time period of the coal-fired unit on the basis of determining starting and stopping of the coal-fired unit, and accordingly, a power generation plan during disconnection and grid connection of the coal-fired unit is made. In order to reduce the influence of start-stop peak regulation on start-stop peak regulation coal-fired units as much as possible, the shut-down time is expected to be as short as possible, and the technical requirements of start-stop peak regulation are met. According to the optimization programming requirements, the start-stop peak regulation optimization programming can be converted into an optimization planning problem, the optimization target is that the start-stop peak regulation time period is as short as possible, and can be expressed as follows:
in the formula (14), the compound represented by the formula (I),
and (3) taking the value of the start-stop state variable for starting and stopping the coal-fired unit at the g time period t as 1 to indicate that the coal-fired unit is in a shutdown peak shaving state at the moment, and taking the value of 0 to indicate that the moment is in shutdown peak shaving. Wherein the content of the first and second substances,
the superscript D is the first letter of the English down
The constraint conditions to be considered comprise peak regulation demand constraint, peak regulation state variable relation constraint and start-stop frequency constraint, wherein the peak regulation demand constraint requires that the start-stop peak regulation capacity provided by starting and stopping the coal-fired unit is greater than the start-stop peak regulation demand in each period, the peak regulation state variable relation constraint is used for defining the relation among the start-stop state variable, the start-stop state variable and the stop state variable, and the start-stop frequency constraint requires that the coal-fired unit provides 1 start-stop at most, which can be expressed as:
in the formulae (15) to (17),
starting state variables and stopping state variables of the coal-fired unit g time period t are both state variables with the value of 0 or 1, the starting state variable value of 1 indicates that the coal-fired unit is converted from stopping to being connected to the grid at the moment, and the stopping state variable value of 1 indicates that the coal-fired unit is converted from being connected to the grid to stopping at the moment. Wherein the content of the first and second substances,
the superscript s is the first letter to start an english start,
the superscript E is the stop english end initial.
By taking the formula (14) as an optimization target and the formulas (15) to (17) as constraint conditions, a start-stop peak-shaving optimization compilation model can be constructed, and the model can be solved by adopting planning methods such as a branch-and-bound method. According to the model solution result, the power generation plan of the start-stop peak shaving coal-fired unit is 0 in the stop peak shaving period, 1-2 hours are generally reserved as the start-stop transition period of the start-stop peak shaving coal-fired unit respectively according to the declared start-stop and stop curves, the coal-fired unit generates power according to the start-stop or stop curves in the transition period, and the power generation plan is the start-stop or stop curves. And (4) taking the power generation plans of the shutdown peak shaving period and the transition period as boundary conditions to be carried into the step S1, recalculating the economic dispatch without considering the deep peak shaving of the coal-fired unit, and realizing the effective connection of the start-stop peak shaving and the economic dispatch.
Step S6: deep peak shaving optimization compilation
The implementation purpose of the step is to optimally arrange a power generation plan of the coal-fired unit in a deep peak shaving period according to the peak shaving requirement of the whole network. In the embodiment, for the area where the peak shaving auxiliary service market is established, an optimized target is constructed and optimized to compile a deep peak shaving time period power generation plan by taking the lowest deep peak shaving cost as a target according to market trading rules, and for the area where the peak shaving auxiliary service market is not established, the power generation plan is compiled according to a 'three-public scheduling' principle without influencing the main innovative content of the invention.
The coal-fired unit should share the demand of the full-network deep peak regulation according to the principle of equal load rate, and considering that the deep peak regulation capacities of different coal-fired units are different, the deep peak regulation optimization compilation optimization target is the target of the highest deep peak regulation quantity balance of the coal-fired unit, and can be expressed as follows:
in the formula (18), the reaction mixture,
the deep peak regulation capacity C of the coal-fired unit in the g period tgInstalled capacity of coal-fired unit g, CFIs the sum of the capacities of the whole-screen coal burner assembling machine,
and the unit set which does not participate in start-stop peak regulation in the coal-fired units is shown. Wherein the content of the first and second substances,
the superscript P is the first letter of peak shaving English, C is the first letter of capacity English capacity, and the superscript F is the first letter of fire power English fire. Then
Representing the peak shaving load rate of the coal-fired unit g,
and averaging the peak load regulation rate of the whole network for the period.
The constraint condition to be considered is mainly peak regulation capacity constraint, and the depth peak regulation capacity provided by each coal-fired unit is required to be not more than the depth regulation minimum output range, which can be expressed as:
and (3) by taking the formula (18) as an optimization target and the formula (19) as a constraint condition, constructing a deep peak shaving optimization compilation model of the coal-fired unit. The model can be directly solved by adopting a simplex method, and technical obstacles do not exist for the technical personnel in the field, so the solving process is not repeated herein.
Step S7: generating a power generation plan
And (4) correcting the day-ahead optimization scheduling compilation result formed by the day-ahead optimization scheduling model without considering the peak shaving of the coal-fired unit by considering the deep peak shaving optimization compilation result to obtain the power generation plans of different types of power supplies of the whole network. The power generation plan of each time interval of the coal-fired unit is a part of a day-ahead optimized scheduling output power generation plan deduction depth peak regulation plan without considering peak regulation, and can be expressed as follows:
in the formula (20), the reaction mixture is,
the g-period t power generation plans of the coal-fired unit after peak regulation correction and without peak regulation are respectively considered, and the superscript F, O is respectively the initials of final English final and initial English original.
The hydropower and wind power generation plan is a day-ahead optimized dispatching output power generation plan without considering peak shaving, namely:
in the formula (21), the compound represented by the formula,
and respectively carrying out time period t power generation plans of the hydroelectric generating set g or the wind power plant g after peak regulation correction and without peak regulation.
The method is mainly characterized in that the optimization programming problem of the start-stop peak regulation of the coal-fired unit is finely considered, and the day-ahead optimization scheduling model of the water-fire-wind mutual aid system considering the start-stop peak regulation of the coal-fired unit is divided into two sub-problems of day-ahead optimization scheduling and start-stop peak regulation optimization, so that the complexity of the original problem is reduced, and the efficient solution of the original mixed integer programming problem is realized. The improvement of the optimization model involved in the steps by combining various market modes and scheduling operation requirements should be regarded as the protection scope of the invention.
Any process or method descriptions in flow charts or otherwise herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps in the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, and the program may be stored in a computer readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium. The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made in the above embodiments by those of ordinary skill in the art without departing from the principle and spirit of the present invention.
Claims (9)
1. A day-ahead optimized scheduling method of a water-fire-wind mutual aid system considering the peak shaving of starting and stopping of a coal-fired unit is characterized by comprising the following steps of: the method comprises the following steps:
step S1: day-ahead optimal scheduling without consideration of coal-fired unit peak shaving
On the premise of not considering the starting and stopping of a coal-fired unit and deep peak regulation, optimally designing a power grid power generation plan to determine peak regulation requirements at each time period; the peak regulation demand distribution factor index is introduced into an optimization target to realize the maximization of the whole network operation benefit after the peak regulation influence is considered, the peak regulation demand distribution factor optimization target comprises two parts, the first part is the maximum peak regulation demand minimum to avoid starting and stopping peak regulation as far as possible, and the second part is the minimum total amount of the regulation demand to reduce the peak regulation cost;
step S2: peak shaver demand statistics
According to the solving result of the step S1, the peak shaving requirements of the system in each time period are statistically analyzed, and an optimal scheduling scheme which meets the lowest total power grid electricity purchasing cost and has the most reasonable peak shaving requirement distribution factor can be obtained through the step S1, wherein the optimal result is the peak shaving requirements in each time period;
step S3: start-stop peak shaving demand determination
The implementation purpose of the step is to judge whether the start and stop of the unit need to be arranged according to the full-network deep peak regulation capacity;
step S4: coal-fired unit capable of determining start-stop peak shaving
Optimizing and compiling the start-stop peak regulation of the coal-fired unit according to the full-network start-stop peak regulation requirement;
step S5: start-stop peak regulation optimization compilation
On the basis of determining starting and stopping of the coal-fired unit, further determining the shutdown period of the coal-fired unit, and making a power generation plan during splitting and grid connection of the coal-fired unit;
step S6: deep peak shaving optimization compilation
Optimally arranging a power generation plan of a coal-fired unit at a deep peak shaving period according to the peak shaving requirement of the whole network;
step S7: generating a power generation plan
And (4) correcting the day-ahead optimization scheduling compilation result formed by the day-ahead optimization scheduling model without considering the peak shaving of the coal-fired unit by considering the deep peak shaving optimization compilation result to obtain the power generation plans of different types of power supplies of the whole network.
2. The method for optimizing and scheduling the water, fire and wind mutual aid system in the day ahead by considering the start-stop peak regulation of the coal-fired unit according to claim 1, wherein the method comprises the following steps: in step S1, the optimization objective after introducing the peak shaver demand distribution factor includes two parts, which may be expressed as:
in the formula (1), NG is the number of units of the whole network, NT is the number of optimized time segments, Delta T is the corresponding time interval, and pg(P) is the declaration price of the unit under different power generation output forces P,
is the planned generated output, P, of the unit at the g time period tt CIs the peak shaver requirement for time period t.
Are respectively purchasedThe weight coefficient of the electricity cost optimization target item and the peak regulation demand distribution factor optimization target item,
the maximum peak shaving demand and the total amount of the adjustment demand in the peak shaving demand distribution factors are respectively.
3. The day-ahead optimized scheduling method of the water-fire-wind mutual aid system considering the start-stop peak shaving of the coal-fired unit according to claim 1 or 2, characterized in that: in step S1, the constraint conditions include a power balance constraint, a network transmission constraint, and a unit operating characteristic constraint.
The power balance constraint requires that the generated power in each time interval should be balanced with the load demand, and if the minimum output limit of the unit is exceeded, the generated power is balanced by the reduction amount of the generated power, which can be expressed as:
in the formula (2), NB represents the number of system nodes,
load prediction for a time period t of a node b;
network transmission constraints require that the operating section flow at each time interval does not exceed the transmission limit, which can be expressed as:
in the formula (3), the reaction mixture is,
upper and lower limit values of transmission capability of operation section s, GSDFs,g、GSDFs,bRespectively are power transfer distribution factors of the unit g, the node b and the operation section s;
the unit operation characteristic constraint refers to the self output variation characteristics required to be met by different types of units such as hydropower, thermal power, wind power and the like.
4. The method for optimizing and scheduling the water, fire and wind mutual aid system in the day ahead by considering the start-stop peak regulation of the coal-fired unit according to claim 1, wherein the method comprises the following steps: in the step S3, because the deep peak shaving cost of the coal-fired unit is much lower than that of the start-stop peak shaving, when the deep peak shaving capability can meet the peak shaving requirement of the power grid, the start-stop peak shaving is not needed; the coal-fired unit deep peak shaving capability is the difference between the minimum technical output and the deep-shaving minimum output, and the full-network deep peak shaving capability is the sum of the deep peak shaving capabilities of all the coal-fired units, and can be expressed as:
in the formula (9), PPAIn order to realize the full-network deep peak regulation capability,
the minimum output force is deeply adjusted for the coal-fired unit g, and g belongs to f and represents all thermal power generating units;
if the full-network depth peak regulation capacity at any time interval is greater than the depth peak regulation demand, the unit start-stop peak regulation is not needed, otherwise, the unit start-stop peak regulation is needed, and the judgment conditions can be expressed as follows:
PPA≥Pt C (10)
if the determination condition in the expression (10) is satisfied in any period, the process proceeds to step S6, otherwise, the process proceeds to step S4.
5. The method for optimizing and scheduling the water, fire and wind mutual aid system in the day ahead by considering the start-stop peak regulation of the coal-fired unit according to claim 1, wherein the method comprises the following steps: in step S4, the full-network start-stop peak shaving requirement is a difference between the full-network deep shaving capability and the time period when the full-network peak shaving requirement cannot be met, and may be represented as:
in the formula (11), Pt SNThe full-network start-stop peak regulation requirement is met in a time period t;
considering that the coal-fired unit is converted into the start-stop peak regulation after providing the deep peak regulation, the peak regulation capability which can be increased is the minimum output of the deep peak regulation, and the coal-fired unit which needs to provide the start-stop peak regulation service is the combination of the coal-fired units which can just meet the maximum start-stop peak regulation requirement of the whole network in each period according to the sequence of the sum of the start-stop peak regulation capabilities, and can be expressed as follows:
in the formulas (12) to (13), the sum of the start-stop peak regulation capacities of the front gs-1 coal-fired units is smaller than the maximum start-stop peak regulation requirement of the whole network, and the sum of the start-stop peak regulation capacities of the front gs coal-fired units is larger than the maximum start-stop peak regulation requirement of the whole network, so that the front gs are the start-stop peak regulation units.
6. The method for optimizing and scheduling the water, fire and wind mutual aid system in the day ahead by considering the start-stop peak regulation of the coal-fired unit according to claim 1, wherein the method comprises the following steps: in step S5, in order to reduce the influence of start-stop peak shaving on start-stop peak shaving coal-fired units as much as possible, it is desirable that the shutdown period is as short as possible, and the requirements of start-stop peak shaving technology are met, and according to the optimization programming requirements, the start-stop peak shaving optimization programming can be converted into an optimization planning problem, and the optimization target is that the start-stop peak shaving period is as short as possible, and can be expressed as:
in the formula (14), the compound represented by the formula (I),
starting and stopping a coal-fired unit at a g time period t, wherein the starting and stopping state variable takes a value of 1 to indicate that the coal-fired unit is in a shutdown peak shaving state at the moment, and takes a value of 0 to indicate that the moment is in shutdown peak shaving;
the constraint conditions to be considered comprise peak regulation demand constraint, peak regulation state variable relation constraint and start-stop frequency constraint, wherein the peak regulation demand constraint requires that the start-stop peak regulation capacity provided by starting and stopping the coal-fired unit is greater than the start-stop peak regulation demand in each period, the peak regulation state variable relation constraint is used for defining the relation among the start-stop state variable, the start-stop state variable and the stop state variable, and the start-stop frequency constraint requires that the coal-fired unit provides 1 start-stop at most, which can be expressed as:
in the formulae (15) to (17),
starting state variables and stopping state variables of the coal-fired unit at the g time period t are both state variables with the value of 0 or 1, the starting state variable value of 1 indicates that the coal-fired unit is converted from stopping to being connected to the grid at the moment, and the stopping state variable value of 1 indicates that the coal-fired unit is converted from being connected to the grid to stopping at the moment;
and (3) by taking the formula (14) as an optimization target and the formulas (15) to (17) as constraint conditions, constructing a start-stop peak-shaving optimization compilation model and solving the model.
7. The method for optimizing and scheduling the water, fire and wind mutual aid system in the day ahead by considering the start-stop peak shaving of the coal-fired unit according to claim 6, wherein: according to the solving result of the start-stop peak shaving optimization compilation model, the power generation plan of the start-stop peak shaving coal-fired unit is 0 in the stop peak shaving period, 1-2 hours are reserved respectively as the start-stop transition period according to the declared start-stop and stop curves, the coal-fired unit generates power according to the start-stop or stop curves in the transition period, the power generation plan is the start-stop or stop curve, the stop peak shaving period and the transition period power generation plan are taken as boundary conditions to be brought into the step S1, the economic dispatch without considering the deep peak shaving of the coal-fired unit is recalculated, and the effective connection of the start-stop peak shaving and the economic dispatch can be realized.
8. The method for optimizing and scheduling the water, fire and wind mutual aid system in the day ahead by considering the start-stop peak regulation of the coal-fired unit according to claim 1, wherein the method comprises the following steps: in step S6, the coal-fired unit should share the demand of deep peak shaving of the whole network according to the equal load rate principle, and considering that different coal-fired units have different deep peak shaving capabilities, the deep peak shaving optimization compilation optimization target is the target of the highest balance of the deep peak shaving amount of the coal-fired unit, and can be expressed as:
in the formula (18), the reaction mixture,
the deep peak regulation capacity C of the coal-fired unit in the g period tgInstalled capacity of coal-fired unit g, CFIs the sum of the capacities of the whole-screen coal burner assembling machine,
representing a set of units which do not participate in starting, stopping and peak shaving in the coal-fired units;
indicating coal-fired unitsg of the peak load rate of the peak load,
the average peak load regulation rate of the whole network in the time period;
the constraint condition to be considered is peak regulation capacity constraint, and the requirement that the deep peak regulation capacity provided by each coal-fired unit does not exceed the deep regulation minimum output range can be expressed as follows:
and (3) by taking the formula (18) as an optimization target and the formula (19) as a constraint condition, constructing a deep peak regulation optimization compilation model of the coal-fired unit and solving the deep peak regulation optimization compilation model.
9. The method for optimizing and scheduling the water, fire and wind mutual aid system in the day ahead by considering the start-stop peak regulation of the coal-fired unit according to claim 1, wherein the method comprises the following steps: in step S7, the power generation plan of the coal-fired unit at each time interval should be a part of the power generation plan deduction depth peak regulation plan output by the day-ahead optimized scheduling without considering peak regulation, and may be represented as:
in the formula (20), the reaction mixture is,
respectively performing g-time t power generation plans of the coal-fired unit after peak regulation correction and without peak regulation;
the hydropower and wind power generation plan is a day-ahead optimized dispatching output power generation plan without considering peak shaving, namely:
in the formula (21), the compound represented by the formula,
and respectively carrying out time period t power generation plans of the hydroelectric generating set g or the wind power plant g after peak regulation correction and without peak regulation.
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