CN110601267A - Reward and punishment mechanism for guiding wind power plant to participate in source-network coordination - Google Patents
Reward and punishment mechanism for guiding wind power plant to participate in source-network coordination Download PDFInfo
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- CN110601267A CN110601267A CN201910953452.4A CN201910953452A CN110601267A CN 110601267 A CN110601267 A CN 110601267A CN 201910953452 A CN201910953452 A CN 201910953452A CN 110601267 A CN110601267 A CN 110601267A
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Abstract
The invention discloses a reward and punishment mechanism for guiding a wind power plant to participate in source-network coordination, which is used for relieving the problem of power deviation in the scheduling of a new energy power system. The reward and punishment mechanism for the wind power plant to participate in the source-network coordination determines reward and punishment amount according to fluctuation conditions and historical fluctuation trends of wind power output power and three influence factors of the wind power output power in total power generation power of a system after an energy storage system is configured by guiding the wind power plant to enable the output power of the energy storage system to meet evaluation indexes. The process for guiding the wind power plant to participate in the source-grid coordination comprises three steps: (1) determining that the wind power output power of the power grid system can meet the evaluation index of source-grid coordination; (2) establishing a reward and punishment mechanism model, and analyzing the influence of the wind power fluctuation rate and the wind power generation ratio on the reward and punishment factors; (3) analyzing the influence of the historical variation trend of the wind power fluctuation rate on a reward and punishment mechanism, and further correcting the reward and punishment model; (4) and selecting an optimization algorithm to determine the capacity of the energy storage system so as to optimize the economic target of the wind power plant. The reward and punishment mechanism provided by the invention is used for solving the problem that the wind power station abandons wind or influences the safe operation of a power system due to the deviation of a wind power output power curve and a power grid dispatching curve caused by wind power fluctuation and uncertainty in the large-scale wind power grid connection process.
Description
Technical Field
The invention relates to the field of new energy power system scheduling and wind power plant participation 'source grid coordination', in particular to a reward and punishment mechanism for guiding a wind power plant to reduce wind power output power fluctuation.
Background
At present, due toWind power is intermittent, fluctuating and uncertain, wind power integration affects the operational reliability and the power quality of a power system, and the control capability of a power grid dispatching department on wind power output power is also seriously weakened. In a high wind power permeability system, wind power has a back peak regulation characteristic under the influence of natural condition change, and when the output of new energy exceeds the regulation range of the system, the output must be controlled to ensure the dynamic balance of the system, but the phenomenon of 'wind abandon' occurs because the wind power is limited to be delivered due to insufficient regulation capacity of a thermal power generating unit. After the new energy is accessed into the power system in a high proportion, the burden of system power regulation is increased, and the conventional power supply needs to change along with the load and balance the output fluctuation of the new energy. In wind power integration, wind power plants mainly pay attention to the on-grid power, and a power grid needs to maintain supply and demand balance all the time, so that the requirements on safety, reliability and the like are met. The two obviously conflict in grid connection reliability and economic benefit. After the energy storage system with a certain capacity is configured in the wind power plant, the wind power plant can have certain adjusting capacity, so that the wind power plant can actively participate in power grid dispatching, and the wind power consumption capacity can be improved. However, due to the limitation of the current technical development, the energy storage device has high cost and operation cost, and the configuration of energy storage creates an obstacle to the economic operation of the wind power plant. Therefore, economic benefits of wind power plant configuration energy storage need to be comprehensively considered through a reward and punishment mechanism, and the purpose is to achieve the state of power coordination between the wind power plant and the power system.
Disclosure of Invention
Aiming at the problem that the output power of the wind power plant is deviated from a power grid dispatching curve, the method provides a reward and punishment mechanism for guiding the wind power plant to actively participate in source-network coordination by a power grid company. The reward and punishment mechanism for the wind power plant to participate in the source-network coordination determines reward and punishment amount according to fluctuation conditions and historical fluctuation trends of wind power output power and three influence factors of the wind power output power in total power generation power of a system after an energy storage system is configured by guiding the wind power plant to enable the output power of the energy storage system to meet evaluation indexes. The method comprises three steps.
Step 1: determining that the wind power output power of the power grid system can meet the evaluation indexes of source-grid coordination, including wind power fluctuation rate and wind power capacity reliability;
step 2: establishing a reward and punishment mechanism model, and analyzing the influence of the wind power fluctuation rate and the wind power generation ratio on the reward and punishment factors;
and step 3: analyzing the influence of the historical variation trend of the wind power fluctuation rate on a reward and punishment mechanism, and further correcting the reward and punishment model;
and 4, step 4: and selecting an optimization algorithm to determine the capacity of the energy storage system so as to optimize the economic target of the wind power plant.
Drawings
Fig. 1 is a reward and punishment mechanism framework diagram for guiding a wind power plant to participate in source grid coordination in the invention.
FIG. 2 is a graph of the variation trend type of the output power fluctuation rate of the wind farm in the present invention.
FIG. 3 is a schematic diagram of wind farm output power and dispatch power in the present invention.
Detailed Description
The present invention will be described in detail with reference to the accompanying drawings.
Step 1, determining that the wind power output power of a power grid system can meet evaluation indexes of source-grid coordination, wherein the evaluation indexes comprise wind power fluctuation rate and wind power capacity reliability, and two indexes of the wind power fluctuation rate and the wind power capacity reliability are defined below.
The wind power fluctuation rate is defined as the standard deviation of the fluctuation variation of the wind power output power, and reflects the stability of the fluctuation variation. Wind power fluctuation greatly affects the stability of a power system in wind power integration, and the reduction of the wind power fluctuation rate is beneficial to the participation of a wind power plant in source-grid coordination, so that the fluctuation rate is an important index for evaluating the quality of wind power. The calculation formula of the wind power fluctuation rate is as follows:
in the formula (I), the compound is shown in the specification,is as followsiA scheduling period andi-1 scheduling period wind power fluctuation variation,is as followsiThe wind power output power of each scheduling period,is as followsi-wind power output for 1 scheduling period,P ave is the average value of the fluctuation range of the wind power,nis the total number of scheduling periods.
The wind power capacity reliability is defined as the proportion of the capacity of the wind power generating set which can be regarded as a conventional set to the installed wind power capacity on the premise of equal reliability. The reliability of wind power capacity is mostly understood from both the power generation side and the load side in the literature: 1) the power generation side: the method comprises the steps of equivalently enabling a wind turbine generator to be a conventional generator with certain forced outage rate by taking the unchanged reliability of a system as a measurement index, and calculating the capacity of the conventional generator which can be replaced by the conventional generator; 2) and (3) loading side: under the same reliability index, the difference of the load which can be borne by the system under the condition of wind power and no wind power exists, namely the effective load capacity of the wind power.
For the wind power plant with fixed planned output power in each scheduling period, the calculation formula of the capacity reliability is as follows:
in the formula:in order to install the capacity for the wind power plant,is the credible capacity of the wind power plant,the capacity of the wind turbine can be equivalent to that of a conventional wind turbine.
The wind power capacity reliability is an important index for measuring the contribution of wind power to the reliability of the power system. The capacity reliability is used as an evaluation index, so that the predictability of the output power of the wind power plant can be accurately evaluated, and the accuracy of the power system planning is improved.
And 2, establishing a reward and punishment mechanism model, and analyzing the influence of the wind power fluctuation rate and the wind power generation ratio on the reward and punishment factors. The expression of the reward and punishment mechanism is expressed as follows: rewarding the wind power plant when the wind power fluctuation rate and the wind power capacity reliability of the wind power plant meet the reference values; and if one index in the wind power field fails to meet the reference value, punishing the wind power field.
In the formula (I), the compound is shown in the specification,Kis the reward and punishment coefficient of the game,K rin order to be the reward factor,K r≥1；K pin order to be a penalty factor,K r<0；the reference value of the wind power fluctuation rate is obtained;and the reference value of the reliability of the wind power capacity is obtained.
The wind power plant wind resource has complex change conditions, and the output power of the wind power plant is influenced in seasonal change, weather change and other aspects, so that the reward penalty coefficient needs to be further corrected. The influence of wind power fluctuation rate and wind power generation duty ratio on reward and punishment factors is analyzed.
The reward factor decreases as the wind wave power increases; since the penalty factor is less than 0, the penalty factor decreases with the increase of the wind wave dynamic rate, and the absolute value of the penalty factor decreases with the windThe radio wave mobility increases. Controlling the fluctuation rate of the wind power output power at a reference value by the wind power plantWhen the wind power station is within the preset time, rewarding the wind power station; and on the contrary, when the fluctuation rate exceeds the reference value, punishment is carried out on the wind power plant, and the punishment degree is higher when the fluctuation rate is higher.
When the ratio of the generated energy of the wind power plant to the total generated energy of the system is larger, the influence of the electric energy quality of the wind power on the system is larger, and therefore the rewarding and punishing strength is increased. On the contrary, in the season of wind resource scarcity, the ratio of the generated energy of the wind power plant to the total generated energy of the system is small, and the rewarding and punishing force is reduced. Analyzing the influence of wind power fluctuation rate and wind power generation ratio on reward and punishment factors, and correcting as follows:
wherein the content of the first and second substances,
in the formula (I), the compound is shown in the specification,is as followsiThe deviation rate of each scheduling period is defined as the wind power output powerAnd scheduling powerThe ratio of the difference value to the planned output power is used for measuring the accuracy of the output power of the wind power plant; the threshold value of the wind power plant power deviation which can be accepted by the power grid company is determined by a dispatching department of the power grid company.
And 3, correcting the reward and punishment model according to the historical variation trend of the wind power fluctuation rate. The study on the variation trend of the fluctuation rate of the adjacent scheduling period of the wind power output power can reflect the spontaneous adjustment capability of the wind power plant and the enthusiasm of participating in source-grid coordination to a certain extent, so that the reward and punishment mechanism also needs to consider the variation trend of the fluctuation rate and is further optimized through the analysis on the variation trend.
And selecting the wind power fluctuation rates of continuous adjacent scheduling periods to draw a change trend curve, wherein the change types are divided into 6 cases, as shown in the attached figure 1. The A-type fluctuation rate is in a descending trend as a whole; the B-type fluctuation rate is in an overall rising trend; the inflection point appears on the CD type fluctuation curve, the fluctuation rate is increased and then reduced, the fluctuation rate of the C type tail end is higher than the fluctuation rate of the initial end, and the fluctuation rate of the D type tail end is lower than the fluctuation rate of the initial end; the EF type fluctuation curve also has an inflection point, the fluctuation rate is increased and then decreased, the E type tail end fluctuation rate is lower than the initial end fluctuation rate, and the F type tail end fluctuation rate is higher than the initial end fluctuation rate.
Analysis on the 6 types of variation in fig. 2 shows that when the fluctuation rate at the tail end is lower than that at the start end, the fluctuation rate of the wind farm is continuously reduced, which is an ideal situation. The appearance of the inflection point represents the aggravation of wind power fluctuation, and changes the trend of change: when even inflection points appear in the curve, the trend is unchanged; when an odd number of inflection points appear in the curve, the trend changes. Therefore, the variation trend of the output power fluctuation rate of the wind power plant in the whole dispatching period can be described by analyzing the fluctuation rate of the starting end and the tail end and the number of inflection points in the fluctuation rate variation trend curve.
The trending factor is incorporated hereinThe influence of the variation trend of the fluctuation rate of the output power of the wind power plant on the reward punishment mechanism is described. Analyzing the curve variation trend, and rewarding the wind power plant when the fluctuation rate is in a monotone reduction trend; on the contrary, if the fluctuation rate is in a monotonous increasing trend, punishing the wind power plant; and when the fluctuation rate variation trend has an inflection point, punishing the wind power plant according to the fluctuation rate variation.
Wherein the content of the first and second substances,
in the formula (I), the compound is shown in the specification,is as followsA trend factor for each of the scheduling periods,is a condition parameter for distinguishing the variation trend of AB class and CDEF class;is a corner penalty coefficient for CDEF-like variation trends.
The reward and punishment factors are corrected by introducing two indexes of wind power fluctuation rate and wind power plant generating capacity ratioAnd introducing a trend factor after analyzing the historical variation trend of the fluctuation rate to finally obtain a mathematical model expression of a reward and punishment mechanism, wherein the mathematical model expression is as follows:
in the formula (I), the compound is shown in the specification,I Wfor the generating benefit of wind power field in one day,is the reward and punishment coefficient of the game,in order to consider the trend factor of the historical variation trend of the wind power fluctuation rate,for the first wind farmiThe power generation amount of each scheduling period, and n is the total number of the scheduling periods in one day.
And 4, step 4: and selecting an optimization algorithm to determine the capacity of the energy storage system so as to optimize the economic target of the wind power plant. The capacity of the energy storage system is determined by utilizing a modern optimization algorithm, and the capacity determination method mainly comprises a particle swarm algorithm, simulated annealing, a genetic algorithm, an ant colony algorithm, an artificial neural network and the like. Fig. 3 is a schematic diagram of output power and scheduling power of a wind farm, and the schematic diagram shows that after energy storage is configured in the wind farm, the output power of the wind farm is closer to a power scheduling curve of a power grid than the output power of the wind farm without the energy storage.
Claims (6)
1. A reward and punishment mechanism for guiding a wind power plant to participate in source-grid coordination is used for relieving the problem of deviation in scheduling of a new energy power system, and is characterized in that the reward and punishment mechanism is executed to relieve the wind abandoning problem of the wind power plant and improve the wind power grid-connected rate, and the method comprises the following steps:
(1) determining that the wind power output power of the power grid system can meet the evaluation index of source-grid coordination;
(2) establishing a reward and punishment mechanism model, and analyzing the influence of the wind power fluctuation rate and the wind power generation ratio on the reward and punishment factors;
(3) analyzing the influence of three factors of historical change trend on a reward and punishment mechanism, and further correcting the reward and punishment model;
(4) and selecting an optimization algorithm to determine the capacity of the energy storage system so as to optimize the economic target of the wind power plant.
2. The reward and punishment mechanism for guiding the participation of the wind power plant in the source-grid coordination according to claim 1, characterized in that the volatility and uncertainty of the wind energy need to be evaluated by introducing the wind power fluctuation rate and the wind capacity credibility in the step (1).
3. The reward and punishment mechanism for guiding the wind power plant to participate in the source-network coordination according to claim 1, wherein in the step (2), a reward and punishment mechanism model needs to be established according to whether the wind power plant meets the evaluation index of the source-network coordination, and then the reward and punishment factor is modified according to three factors, namely the wind power fluctuation rate, the wind power generation duty ratio and the historical change trend.
4. The reward and punishment mechanism for guiding the wind power plant to participate in the source-grid coordination according to claim 1, wherein in the step (3), the cost of the energy storage system configured in the wind power plant and the reward amount obtained by the wind power plant need to be comprehensively measured, and an optimization algorithm is selected to determine the capacity of the energy storage system, so that the fluctuation rate of the output power of the wind power plant is reduced, the quality of the output electric energy is improved, and the optimal source-grid coordination state is achieved.
5. The reward and punishment mechanism for guiding the wind power plant to participate in the source-grid coordination is characterized in that in a power system with high wind power permeability, wind power fluctuation and uncertainty cause deviation between a wind power output power curve and a power grid dispatching curve, so that in order to ensure safe and stable operation of the system, adverse effects of the fluctuation and uncertainty of wind power on wind power grid connection on a power grid are weakened, meanwhile, the amount of waste wind is reduced to ensure the consumption of renewable energy, and the positivity of the wind power plant to participate in the source-grid coordination needs to be improved.
6. The method for improving the enthusiasm of the wind power plant for participating in the source-grid coordination is characterized in that under the guidance of a reward and punishment mechanism, the wind power plant is provided with an energy storage system to smooth the wind power output power, and under the condition that the evaluation requirement is met, the wind power plant obtains corresponding bonus money and is used for running and maintaining the energy storage system according to the specific condition of the output power of the wind power plant, so that a virtuous cycle is formed, and the power coordination state between the wind power plant and a power system is promoted.
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| CN111724259A (en) * | 2020-06-17 | 2020-09-29 | 中国南方电网有限责任公司 | Energy and rotation standby market clearing method considering multiple uncertainties |
| CN111724259B (en) * | 2020-06-17 | 2023-09-01 | 中国南方电网有限责任公司 | Energy and rotary reserve market clearing method considering multiple uncertainties |
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Application publication date: 20191220 |