CN113013928A - Optimized scheduling method of wind-fire-storage combined system - Google Patents
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Abstract
The invention discloses an optimized scheduling method of a wind-fire-storage combined system, which solves the problems that the scheduling of an electric power system is challenged by the existing wind power, a large amount of wind is abandoned, and the optimized scheduling, the stability and the electric energy quality of the electric power system in the operation process are influenced, and has the technical scheme main points that a wind power field uncertainty output model is established, a Latin hypercube sampling method and a scene reduction technology are adopted to process the wind power output scene to generate a wind power output random scene, a wind-fire-storage combined power generation system scheduling model is established, an objective function is combined, an improved particle swarm algorithm is adopted to solve the scheduling model, and after pumped storage is added in a contrastive analysis, the economic safety and the wind power consumption of the system are improved, the wind power consumption can be increased, and the running economy of the thermal power generating unit and the stability of the system can be guaranteed.
Description
Technical Field
The invention relates to a new energy power system optimization technology, in particular to an optimization scheduling method of a wind-fire-pumping and storage combined system.
Background
At the present stage, wind power is accessed into a power grid in a large scale, so that certain positive influence and significance are provided for energy conservation and emission reduction of power grid operation and sustainable development of the economic society, but wind power has randomness, uncertainty and intermittence, so that challenges are brought to scheduling of a power system, and simultaneously, a large amount of abandoned wind is caused, so that certain influence is provided for optimal scheduling, stability and power quality in the operation process of the power system.
Disclosure of Invention
The invention aims to provide an optimal scheduling method of a wind-fire-pumping and storage combined system, which can ensure the running economy of a thermal power generating unit and the stability of the system while increasing the wind power consumption.
The technical purpose of the invention is realized by the following technical scheme:
an optimal scheduling method of a wind-fire-pumping and storage combined system comprises the following steps:
s1, adopting wind power output to accord with Weibull distribution to establish a wind power plant uncertain output model;
s2, processing the wind power output scene by adopting a Latin hypercube sampling method and a scene reduction technology to generate a wind power output random scene;
s3, establishing a wind-fire-storage and extraction combined power generation system scheduling model; establishing a target function according to the lowest operation cost, carbon emission right transaction cost, pollutant punishment cost, wind power generation cost and electric energy shortage cost of the thermal power generating unit; respectively establishing a power system constraint condition, a thermal power unit constraint condition, a wind power unit constraint condition and a pumped storage power station constraint condition;
s4, solving the scheduling model by adopting an improved particle swarm algorithm in combination with the objective function;
and S5, comparing and analyzing the system operation economic safety and the wind power consumption after adding pumped storage.
In conclusion, the invention has the following beneficial effects:
by applying a Latin hypercube sampling method and a scene reduction technology, the inaccuracy of the general prediction of the wind power output can be relieved, and the wind power output is considered more comprehensively when being distributed; adding carbon emission right trade cost and pollutant penalty cost can enable the scheduling result to consider the environmental factors while considering the economical efficiency; the pumped storage power station is added for storing energy, so that redundant wind power can be stored to reduce the abandoned wind volume, electric energy can be timely generated when the electric energy is insufficient, and the effects of peak clipping and valley filling can be achieved, so that the system is safer and more stable to operate.
Drawings
FIG. 1 is a schematic flow diagram of the process;
FIG. 2 is a schematic diagram of wind power variation with wind speed;
FIG. 3 shows 10 wind power output scenarios after the wind power output is reduced;
FIG. 4 is a schematic diagram of the output of each unit and the cost of power generation when the pumping storage exists;
FIG. 5 is a schematic diagram of the output of each unit and the cost of power generation when there is no pumping storage.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
Aiming at the existing problems, the current research content and technology mainly comprise the following aspects:
1. thermal power dispatching is integrated into the wind-storage combined system;
2. the capacity matching of the combined operation of wind power and pumped storage and how to improve the wind power consumption by using pumped storage are researched;
3. the problems of wind power consumption, economic benefit and the like are researched and treated.
Although research has been conducted to solve the problems of wind power consumption and economic benefits, the overall consideration is not comprehensive. The existing research on capacity matching of combined operation of wind power and pumped storage and how to improve wind power consumption by using pumped storage needs to meet certain geographic advantages, and most of the existing research aims at independent and autonomous micro-grids.
Although thermal power dispatching is integrated into a wind-storage combined system, most of the current technical researches still stay at the level of a combined system of wind power and pumped storage, adjustment is mostly considered depending on the flexibility of a thermal power unit, frequent starting and stopping of the thermal power unit is inevitably caused, and the economical efficiency and the safety of power grid operation are influenced. How to coordinate and consider the operation of the wind-fire-pumping and storage combined system, and realizing the stable operation of colleges and universities and the optimal economic benefit while improving the wind power utilization rate is the problem to be solved by the research.
According to one or more embodiments, an optimal scheduling method for a wind-fire-storage combined system is disclosed, as shown in fig. 1, and includes the following steps:
and S1, establishing a wind power plant uncertain output model, and establishing a probability model by adopting wind power output according with Weibull distribution.
And S2, processing the wind power output scene by adopting a Latin hypercube sampling method and a scene reduction technology to generate a wind power output random scene.
S3, establishing a wind-fire-storage and extraction combined power generation system scheduling model; establishing a target function according to the lowest operation cost, carbon emission right transaction cost, pollutant punishment cost, wind power generation cost and electric energy shortage cost of the thermal power generating unit; and respectively establishing a power system constraint condition, a thermal power unit constraint condition, a wind power unit constraint condition and a pumped storage power station constraint condition.
And S4, solving the scheduling model by adopting an improved particle swarm algorithm in combination with the objective function.
And S5, comparing and analyzing the system operation economic safety and the wind power consumption after adding pumped storage.
In particular, the method comprises the following steps of,
the method adopts wind power output conforming to Weibull distribution to establish a probability model, and the distribution function is as follows:
wherein k is a shape parameter of Weibull distribution and influences the curve shape of the distribution function, and c is a scale parameter of Weibull distribution and reflects the size of the average wind speed.
The wind power output is mainly determined by the wind speed, and as shown in fig. 2, the wind power output is mathematically expressed as:
in the formula, pwrThe rated installed capacity of the fan; v is the actual wind speed; v. ofinTo cut into the wind speed; v. ofoutCutting out the wind speed;vr is the rated wind speed.
In step S2, the latin hypercube sampling method and the scene reduction technique are used to process the wind power output scene to generate a wind power output random scene, as shown in fig. 3, and finally 10 target scenes of wind power output within 24 hours are used for displaying and analyzing.
The method specifically comprises the following steps of establishing a target function with the lowest operation cost, carbon emission right transaction cost, pollutant punishment cost, wind power generation cost and electric energy shortage cost of the thermal power generating unit:
s31, establishing an objective function:
s311, the operating cost of the thermal power generating unit is as follows:
the traditional thermal power generating unit consumes fossil energy in operation, coal consumption cost needs to be considered in a cost function, and the unit operation cost function is as follows:
in the formula, C1The operation cost of the thermal power generating unit is reduced; a isi、bi、ciThe cost coefficient of coal consumption of the ith unit is obtained; t is the total time interval of daily scheduling, and 24h is taken; n is the total number of the thermal power generating units; pGitAnd the output power of the ith unit at the moment t.
S312, carbon emission right transaction cost:
when the carbon dioxide emission amount of a power generation enterprise reaches the distribution capacity, the carbon emission right needs to be continuously purchased from carbon emission centers of various regions, and the carbon emission transaction cost is as follows:
in the formula, C2Trading carbon emissions for market current market price, RbmCoefficient of coal consumption, R, for power supplyco2Is the carbon dioxide conversion factor.
S313, penalty cost of pollutants
The total penalty cost for a contaminant is:
s314, wind power generation cost
The wind power generation operation cost comprises three parts: normal operation cost, spinning reserve capacity penalty cost and wind abandonment cost, the function of which is as follows:
in the formula, C4For the total operating cost of the wind power plant, NwIs the total number of wind generators, diFor the grid price of the ith wind farm, giA wind curtailment penalty coefficient, p, for the ith wind farmwitThe grid-connected electric quantity p of the ith wind power plant in the t periodwritAnd (4) predicting the output of the ith wind power plant in the t period.
S315, electric energy shortage cost
C5＝ph·h
In the formula, C5To a deficiency of cost, phThe power is insufficient, and h is a penalty coefficient;
s32, respectively establishing a power system constraint condition, a thermal power unit constraint condition, a wind power unit constraint condition and a pumped storage power station constraint condition:
s321, power balance constraint:
in the formula, P1tAnd the load of the power grid system at the moment t.
S322, rotating reserve capacity constraint:
the rotating reserve capacity of the power grid is the basis of safe and stable operation of the power grid; the rotating reserve capacity is related to uncertainty information such as wind power output prediction error, and the uncertainty of wind power is processed by adopting an opportunity constraint planning method, which comprises the following steps:
positive spinning reserve capacity constraint:
in the formula, PGmaxitThe maximum output at the moment t of the ith thermal power generating unit, KlupIs a positive coefficient of fluctuation, K, of the load of the grid systemWupFor positive rotational reserve factor, beta, of wind power1As a confidence level.
Negative spin reserve capacity constraint:
in the formula, PGminitIs the minimum output, K, of the ith thermal power generating unit at the moment tldownNegative fluctuation coefficient, beta, of the load of the grid system2As a confidence level.
S323, constraint conditions of thermal power generating unit
Unit output restraint:
PGmini≤PGit≤PGmaxi
and (3) unit climbing rate constraint:
-Rdi≤PGit-PGi(t-1)≤Rui。
s324, wind turbine generator constraint conditions
The output constraint conditions of the wind turbine generator are as follows:
0≤pwrit≤pw
in the formula, pwThe maximum output of the wind power plant.
S325, constraint conditions of pumped storage power station
Force restraint:
in the formula (I), the compound is shown in the specification,
representing the generated power of the pumped storage power station in the t period if
The pumped storage power station is in a pumped state;
the maximum power generation output and the maximum pumping power of the pumped storage unit are the same and equal to the installed capacity.
Reservoir energy balance constraint:
setting the conversion efficiency of pumped storage to etaGTaking 75%, keeping the total energy of the single-day reservoir balanced, namely, keeping the pumping balance of the pumped storage unit, wherein the generated energy is equal to 75% of the pumped storage:
in the formula, TGIs the operation time period under the pumped storage power generation working condition.
As shown in fig. 4 and 5, the power output and the power generation cost of each unit with and without the pumping storage are shown, in each graph, (a) part of the graph shows the power output situation of each unit, pg1-10 of the graph are 10 thermal power units, the abscissa is time (24h), the ordinate is the power output value, and (b) part of the graph shows the power generation cost. The results show that when no pumping storage exists, the overall output of each unit is increased, the load is generally increased obviously, and the power generation cost is greatly increased.
Step S4, combining with the objective function, solving the scheduling model by adopting an improved particle swarm optimization, and obtaining the beneficial effect of the pumped storage power station on the scheduling system, wherein the concrete implementation steps of the improved particle swarm optimization are as follows:
s41, let t equal to 0, and randomly generate initialization particle population PtCalculating the objective function value corresponding to each particle, and adding the non-inferior solution into the non-inferior solution set NPt；
S42, finding out the initial individual optimal value of the particles
And global optimum
S43, updating the speed and position of the particles to form a next subgroup, and finding out the adjusted particle swarm individual extremum
S44, maintaining the external file by using the new non-inferior solution to form the external file of the next iteration, and simultaneously selecting a global extreme value for each particle
And S45, if t is t +1, stopping searching if the termination condition is met, and otherwise, returning to the step S43.
In the multi-objective optimization problem, a plurality of global extrema are possible to exist and are not influenced by the reason that the global optimal value is not unique. Therefore, in the process of improving the operation of the particle swarm optimization, a new research direction is how to select global values and individual values, maintain internal and external files, ensure that particles are always in a feasible domain and the like. At present, researchers have proposed various methods for solving the problem of global extremum of particles. The fitness is defined for each interval divided by the clusters, one interval is selected according to a wheel disc method, and then an individual of an external particle swarm is randomly selected as a global optimum value.
At present, the energy storage technology is an effective means for solving the problem of power grid dispatching, so that the stable operation of a power grid can be ensured, the air abandon rate can be reduced, and the energy storage system plays an important role in improving the flexibility of a system. In terms of development, the pumped storage power station is an energy storage device with large capacity, mature technology and low cost. The invention provides a wind-fire-pumped storage combined scheduling model, simultaneously considers energy conservation and emission reduction, meets the requirements of lowest environmental cost, lowest wind abandon punishment cost, balanced system power and the like, provides an effective analysis method for the combined scheduling of various renewable energy sources, and verifies by applying an improved particle swarm algorithm.
Because wind power output prediction is a difficulty, the technical scheme adopts a Latin hypercube sampling method and a scene reduction technology to process the wind power output prediction, and firstly 1000 wind power output scenes including the wind power output prediction value and an error value are generated on the basis of the wind power prediction value by utilizing the Latin hypercube sampling. And then, the number of predicted scenes is reduced by using a scene reduction technology, and 10 target scenes are displayed and analyzed, so that the inaccuracy of general prediction on wind power output can be relieved, and the wind power output is considered more comprehensively when being distributed.
Adding carbon emission right transaction cost and pollutant punishment cost when establishing an objective function, so that the economic efficiency and the environmental factors are considered in the scheduling result; the energy-saving wind power generation system is added into a pumped storage power station, the air volume can be greatly reduced, the stable operation of a system containing a thermal power generating unit can be positively influenced, the peak clipping and valley filling effects can be achieved, and the system can be operated more safely and stably.
The present embodiment is only for explaining the present invention, and it is not limited to the present invention, and those skilled in the art can make modifications of the present embodiment without inventive contribution as needed after reading the present specification, but all of them are protected by patent law within the scope of the claims of the present invention.
Claims (4)
1. An optimal scheduling method of a wind-fire-storage combined system is characterized by comprising the following steps:
s1, adopting wind power output to accord with Weibull distribution to establish a wind power plant uncertain output model;
s2, processing the wind power output scene by adopting a Latin hypercube sampling method and a scene reduction technology to generate a wind power output random scene;
s3, establishing a wind-fire-storage and extraction combined power generation system scheduling model; establishing a target function according to the lowest operation cost, carbon emission right transaction cost, pollutant punishment cost, wind power generation cost and electric energy shortage cost of the thermal power generating unit; respectively establishing a power system constraint condition, a thermal power unit constraint condition, a wind power unit constraint condition and a pumped storage power station constraint condition;
s4, solving the scheduling model by adopting an improved particle swarm algorithm in combination with the objective function;
and S5, comparing and analyzing the system operation economic safety and the wind power consumption after adding pumped storage.
2. The optimal scheduling method of a wind-fire-storage combined system as claimed in claim 1, wherein the step S1 specifically includes:
the distribution function is established as
Wherein k is a shape parameter of Weibull distribution and influences the curve shape of the distribution function, and c is a scale parameter of Weibull distribution and reflects the size of the average wind speed;
the wind power output power is expressed as
In the formula, pwrThe rated installed capacity of the fan; v is the actual wind speed; v. ofinTo cut into the wind speed; v. ofoutCutting out the wind speed; v. ofrIs the rated wind speed.
3. The optimal scheduling method of the wind-fire-storage combined system as claimed in claim 1, wherein the step S3 is specifically:
s31, establishing an objective function:
s311, operating cost of thermal power generating unit
The traditional thermal power generating unit consumes fossil energy in operation, coal consumption cost needs to be considered in a cost function, and the unit operation cost function is as follows:
in the formula, C1For the operating cost of the thermal power generating unit, ai、bi、ciTaking 24h as the coal consumption cost coefficient of the ith unit, T as the total time period number of daily scheduling, N as the total number of the thermal power generating units, PGitThe output power of the ith unit at the moment t;
s312, carbon emission right transaction cost
When the carbon dioxide emission amount of a power generation enterprise reaches the distribution capacity, the carbon emission right needs to be continuously purchased from carbon emission centers of various regions, and the carbon emission transaction cost is as follows:
in the formula, C2Trading carbon emissions for market current market price, RbmIn order to supply the power to the coal consumption coefficient,
is the carbon dioxide conversion coefficient;
s313, penalty cost of pollutants
The total penalty cost for a contaminant is:
s314, wind power generation cost
The wind power generation operation cost comprises three parts: normal operation cost, spinning reserve capacity penalty cost and wind abandonment cost, the function of which is as follows:
in the formula, C4For the total operating cost of the wind power plant, NwIs the total number of wind generators, diFor the grid price of the ith wind farm, giA wind curtailment penalty coefficient, p, for the ith wind farmwitThe grid-connected electric quantity p of the ith wind power plant in the t periodwritThe predicted output of the ith wind power plant in the t period;
s315, electric energy shortage cost
C5＝ph·h
In the formula, C5To a deficiency of cost, phThe power is insufficient, and h is a penalty coefficient;
s32, establishing a constraint condition:
s321, power balance constraint:
in the formula, P1tThe load of the power grid system at the moment t;
s322, rotating reserve capacity constraint:
the rotating reserve capacity of the power grid is the basis of safe and stable operation of the power grid; the rotating reserve capacity is related to uncertainty information such as wind power output prediction error, and the uncertainty of wind power is processed by adopting an opportunity constraint planning method, which comprises the following steps:
positive spinning reserve capacity constraint:
in the formula, PG max itThe maximum output at the moment t of the ith thermal power generating unit, KlupIs a positive coefficient of fluctuation, K, of the load of the grid systemWupFor positive rotational reserve factor, beta, of wind power1Is a confidence level;
negative spin reserve capacity constraint:
in the formula, PG min itIs the minimum output, K, of the ith thermal power generating unit at the moment tldownNegative fluctuation coefficient, beta, of the load of the grid system2Is a confidence level;
s323, constraint conditions of thermal power generating unit
Unit output restraint:
PG min i≤PGit≤PG max i
and (3) unit climbing rate constraint:
-Rdi≤PGit-PGi(t-1)≤Rui
s324, wind turbine generator constraint conditions
The output constraint conditions of the wind turbine generator are as follows:
0≤pwrit≤pw
in the formula, pwThe maximum output of the wind power plant;
s325, constraint conditions of pumped storage power station
Force restraint:
in the formula (I), the compound is shown in the specification,
representing the generated power of the pumped storage power station in the t period if
The pumped storage power station is in a pumped state;
the maximum power generation output and the maximum pumping power of the pumped storage unit are the same and equal to the installed capacity of the pumped storage power station;
reservoir energy balance constraint:
setting the conversion efficiency of pumped storage to etaGTaking 75% and keeping the total energy of the single-day reservoir balanced, namely, the pumping and generating balance of the pumped storage unit (the generating capacity is equal to 75% of the pumping capacity):
in the formula, TGIs the operation time period under the pumped storage power generation working condition.
4. The optimal scheduling method of the wind-fire-pumped storage combined system as claimed in claim 1, wherein the step S4 of improving the particle swarm optimization comprises the following specific steps:
s41, let t equal to 0, and randomly generate initialization particle population PtCalculating the objective function value corresponding to each particle, and adding the non-inferior solution into the non-inferior solution set NPt；
S42, finding out the initial individual optimal value of the particles
And global optimum
S43, updating the speed and position of the particles to form a next subgroup, and finding out the adjusted particle swarm individual extremum
S44, maintaining the external file by using the new non-inferior solution to form the external file of the next iteration, and simultaneously selecting a global extreme value for each particle
And S45, if t is t +1, stopping searching if the termination condition is met, and otherwise, returning to the step S43.
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