CN116544951A - Hydropower peak regulation flexibility quantification and scheduling method - Google Patents
Hydropower peak regulation flexibility quantification and scheduling method Download PDFInfo
- Publication number
- CN116544951A CN116544951A CN202310489833.8A CN202310489833A CN116544951A CN 116544951 A CN116544951 A CN 116544951A CN 202310489833 A CN202310489833 A CN 202310489833A CN 116544951 A CN116544951 A CN 116544951A
- Authority
- CN
- China
- Prior art keywords
- peak
- period
- power
- output
- electric quantity
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000033228 biological regulation Effects 0.000 title claims abstract description 51
- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000011002 quantification Methods 0.000 title claims abstract description 9
- 238000010248 power generation Methods 0.000 claims abstract description 26
- 238000004364 calculation method Methods 0.000 claims abstract description 8
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 28
- 230000005611 electricity Effects 0.000 claims description 19
- 230000009191 jumping Effects 0.000 claims description 9
- YTAHJIFKAKIKAV-XNMGPUDCSA-N [(1R)-3-morpholin-4-yl-1-phenylpropyl] N-[(3S)-2-oxo-5-phenyl-1,3-dihydro-1,4-benzodiazepin-3-yl]carbamate Chemical compound O=C1[C@H](N=C(C2=C(N1)C=CC=C2)C1=CC=CC=C1)NC(O[C@H](CCN1CCOCC1)C1=CC=CC=C1)=O YTAHJIFKAKIKAV-XNMGPUDCSA-N 0.000 claims description 8
- 238000004458 analytical method Methods 0.000 claims description 8
- GNFTZDOKVXKIBK-UHFFFAOYSA-N 3-(2-methoxyethoxy)benzohydrazide Chemical compound COCCOC1=CC=CC(C(=O)NN)=C1 GNFTZDOKVXKIBK-UHFFFAOYSA-N 0.000 claims description 4
- 241000196324 Embryophyta Species 0.000 claims description 4
- 230000001105 regulatory effect Effects 0.000 claims description 4
- 238000012163 sequencing technique Methods 0.000 claims description 4
- 240000000736 Amomum maximum Species 0.000 claims description 2
- FGUUSXIOTUKUDN-IBGZPJMESA-N C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 Chemical compound C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 FGUUSXIOTUKUDN-IBGZPJMESA-N 0.000 claims description 2
- 238000009826 distribution Methods 0.000 claims description 2
- 230000003828 downregulation Effects 0.000 claims description 2
- 230000008569 process Effects 0.000 claims description 2
- 230000003827 upregulation Effects 0.000 claims description 2
- 238000013139 quantization Methods 0.000 abstract description 3
- 230000004044 response Effects 0.000 description 3
- 238000009825 accumulation Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 241000272525 Anas platyrhynchos Species 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 239000003653 coastal water Substances 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000004146 energy storage Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 230000001932 seasonal effect Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
- H02J3/144—Demand-response operation of the power transmission or distribution network
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/28—The renewable source being wind energy
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
- H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
- H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
- H02J2310/58—The condition being electrical
- H02J2310/60—Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Theoretical Computer Science (AREA)
- Strategic Management (AREA)
- Power Engineering (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Entrepreneurship & Innovation (AREA)
- Data Mining & Analysis (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Tourism & Hospitality (AREA)
- Game Theory and Decision Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Operations Research (AREA)
- Educational Administration (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Development Economics (AREA)
- Quality & Reliability (AREA)
- Artificial Intelligence (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Control Of Eletrric Generators (AREA)
Abstract
The invention discloses a hydropower peak regulation flexibility quantification and scheduling method, which comprises the following steps: based on the index of the matching degree of the wind power output and the power grid load demand in time, whether the hydropower participates in the power grid peak shaving is flexibly adjusted according to the matching degree of the wind power output and the power grid load demand. Based on the index of the matching degree of the wind power generation amount in the early-late peak period and the electric quantity required by the power grid, the electric quantity gap existing in the early-late peak period after the new energy is connected is considered, so that the scheduling rule of which period is preferentially compensated by the hydroelectric electric quantity is obtained, and the peak regulation capability of the hydropower is exerted to the maximum extent. Based on the hydropower peak regulation capacity quantization method, factors such as forced output, ecological flow and the like of the power station are comprehensively considered, and the peak regulation capacity of the river basin steps is quantized. And generating a hydropower scheduling plan by combining the hydropower quantity priority compensation rule and the quantized hydropower peak regulation capacity. The scheduling plan generated by the method is strong in interpretation and high in calculation speed, and has important reference significance for hydropower scheduling personnel to make a hydropower generation plan.
Description
Technical Field
The invention relates to the field of multi-energy complementary coordination scheduling, in particular to a response of hydropower under wind and light large-scale networking to new energy peak regulation demands, and specifically relates to a hydropower peak regulation flexibility quantification and scheduling method.
Background
Wind power output has the characteristic of anti-peak shaving, and large-scale grid connection of photovoltaic leads to the appearance of a duck curve, and large-scale grid connection of new energy sources represented by wind power and photovoltaic brings great challenges to peak shaving of a novel power system. Besides the approaches of thermal power flexibility transformation, new large-scale energy storage power station creation, demand side management and the like, the conventional hydropower peak regulation capacity is fully utilized, and the method has important practical significance for promoting the efficient consumption of new energy and ensuring the stable operation of the system.
Existing researches on the response of water and electricity to new energy peak shaving demands can be roughly divided into two types: the uncertainty of wind power and photovoltaic output is quantified through scene simulation, uncertainty collection and other methods, and then a joint scheduling model is constructed with hydropower for solving; and the other type of the water and electricity response to the new energy peak regulation requirement is realized through constraint condition setting. Most of the existing researches start from the uncertainty of new energy output, and are coupled with a hydropower construction peak regulation model to obtain a hydropower scheduling plan. However, considering the difficulty of directly optimizing the result of the model, in actual production, the dispatcher is more concerned about key problems such as how large the system peak regulation needs are, how much the hydropower peak regulation capacity is, how to reasonably arrange the hydropower dispatching plan according to the peak regulation capacity supply-demand relation between the hydropower and the new energy. Therefore, the reasonable quantitative index of the hydropower peak regulation capability is provided, and the method has important significance on the peak regulation requirement of hydropower on new energy under a novel electric power system.
Disclosure of Invention
Aiming at the problems and actual engineering demands of dispatching personnel, the technical problem to be solved by the invention is to provide a novel method for quantifying and dispatching the hydropower peak regulation capacity under the electric power system, which can effectively excavate and quantify the hydropower peak regulation capacity, and directly generate a hydropower dispatching plan according to the quantified hydropower peak regulation capacity.
The technical scheme of the invention is as follows:
a method for quantifying and scheduling hydropower peak regulation capacity in a novel electric power system mainly comprises the following steps: and analyzing the wind power output and system load peak-valley matching characteristics, quantifying the river basin step peak regulation capability and generating a hydropower scheduling scheme. And the quantification and the scheduling of the hydropower peak regulation capacity of the novel power system are completed according to the following steps.
The initial calculation conditions comprise wind power historical actual output data, river basin step hydropower historical actual operation data, provincial power grid historical actual load data and step power station basic data.
(1) Peak-valley matching characteristic analysis of wind power output and system load
1) Power grid load characteristic analysis
Step1.1.1: preliminary peak-to-valley period identification based on fuzzy membership function
And carrying out preliminary identification and division on peak-valley time periods of the load by adopting a fuzzy membership function. Assume that a 96-point-a-day load value sequence is l= { L 1 ,…,L t …,L T Using a larger semi-trapezoid membership function to determine the probability P (L) that each period is a peak period on the load curve t ) The method comprises the steps of carrying out a first treatment on the surface of the Determining the probability V (L) that the load of each period is a valley period by adopting a semi-trapezoid membership function with smaller size t ) The calculation formula is as follows:
wherein: l (L) t Load value of the system for t period; l (L) max Is the maximum value of the system load on the same day; l (L) min Is the minimum value of the system load; t (T) all A set of time periods within one scheduling period; m is the total number of time periods within the scheduling period.
Assume that the threshold values of the membership functions of the peak-valley periods are alpha respectively 1 And alpha 2 The sets of peak-to-valley periods are respectively T peak ,T valley ,T flat The number of elements in the peak-to-valley set is m respectively 1 ，m 2 ，m 3 The following formula is given.
Step1.1.2: and correcting the peak-valley period identified by the fuzzy membership function based on the peak-valley period of the historical actual load data of the power grid, and dividing the valley period, the early peak period, the late peak period and the flat period.
2) Wind power output and load matching analysis
Step1.2.1: and calculating the matching of wind power output and load according to the following formula:
wherein: pw (pw) t At tWind power output of the segment, MW; l (L) t The system load of the power grid in the t period is MW; NL (NL) t Removing net load after wind power for t-period power grid load, MW;peak-valley difference, MW, of system load in a scheduling period T;peak-to-valley difference, MW, of the payload in the scheduling period; zeta type toy p And the index is used for measuring the matching degree of wind power output and grid load.
Step1.2.2: according to the historical actual wind power output data and the power grid load data, calculating the matching degree xi of the wind power output and the power grid load according to Step1.2.1 p All xi p And (5) carrying out accumulated frequency sequencing to determine a coefficient delta.
Wherein: delta is the output matching coefficient threshold value of wind power output and load which are rated according to historical data, and the meaning of the expression is that the expression is delta p When the wind power is more than or equal to 1+delta, the wind power is reversely subjected to peak shaving, the peak shaving capacity requirement of the power grid is larger, and the power supply of the power grid is required to participate in peak shaving at the moment; 1-delta < xi p When the wind power is less than 1+delta, the wind power has no influence on the peak shaving capacity requirement of the power grid, and the peak shaving of the power grid water supply is not needed at the moment; when xi p When the wind power is less than or equal to 1-delta, the wind power is in positive peak regulation, and the peak regulation required capacity of the power grid is reduced.
3) Matching degree analysis of peak-valley period electric quantity distribution
And (3) analyzing the matching degree of the wind power generation amount of the early peak period and the late peak period and the required electric quantity of the power grid according to the dividing result of the peak-valley period in the step (1) to obtain a compensation rule of the hydroelectric electric quantity.
Step1.3.1: calculating the matching degree of the wind power generation amount in the early-late peak period and the power grid required electric quantity according to the following steps:
wherein: LE (LE) p1 、LE p2 The power requirements of the early peak period and the late peak period are respectively represented, and MWh is measured; WE (Power of industry) p1 、WE p2 The method comprises the steps of respectively representing wind power generation capacity of an early peak period and wind power generation capacity of a late peak period, and MWh; zeta type toy E And (5) representing the matching degree of the wind power generation amount and the power grid demand electric quantity in the early-late peak period.
Step1.3.2: according to the historical actual wind power output data and grid load data, calculating the matching degree xi of the wind power generation amount in the early-late peak period and the grid required electric quantity according to the Step1.3.1 E All xi E And (5) carrying out accumulated frequency sequencing to determine a coefficient epsilon.
Wherein: epsilon is the electric quantity matching coefficient threshold value of wind power output and load which are rated according to historical data, and the meaning of the expression is that the expression is delta E2 When the electric quantity is more than or equal to 1+epsilon, the water-electricity priority compensation early peak electric quantity requirement; when xi E2 When the electricity quantity is less than or equal to 1-epsilon, the water electricity preferentially compensates the late peak electricity quantity; when 1-epsilon is less than or equal to zeta E2 And when the electricity consumption is less than or equal to 1+epsilon, the water and electricity can perform balanced compensation on the electric quantity demand of the early and late peaks.
(2) Quantification of drainage basin step peak regulation capability
The peak shaving capacity of the hydropower station is quantified as follows:
wherein: eta is the daily average water consumption rate of the power station, m 3 /kW·h；qp eco For the ecological flow of the power station, m 3 /s；Forced output MW of the power station; qp (q) max For maximum power generation flow of power station, m 3 /s；/>Is the installed capacity, MW, of the power station; />The power station is the daily minimum output, MW; />Is the daily maximum output of the power station, MW.
The calculation formulas of the daily peak regulation capacity of the power station, the daily adjustable peak capacity of the power station and the maximum peak duration of the power station are as follows:
wherein:peak regulating capacity, MW, of a power station; />Planning power generation capacity and MWh for the current day of the power station; Δt is the length of the period; />And h is the maximum peak duration of the power station.
(3) Generation of hydropower scheduling schemes
And (3) guiding the generation of a hydropower station scheduling plan based on the matching characteristics of the wind power and the system load in the step (1) and the quantitative index of the hydropower peak shaving capacity in the step (2).
Step3.1: and analyzing the peak-valley matching characteristics of wind power output and system load, and judging whether water power peak regulation and a compensation rule of the water power peak regulation are needed.
Step3.2: quantifying peak regulation capacity of river basin steps, and calculating daily peak regulation capacity of power station with regulation capacityDaily peak-adjustable electric quantity +.>Maximum peak duration->Daily minimum output of power station->And the daily planned power generation of the power station->
Step3.3: a scheduling plan is generated for a power station having a capacity for scheduling. Assuming that the set of time periods in the scheduling period is T, the total number of the time periods is n, and the sunrise power set of the power station m is P m Up-regulation of plant m is used asThe downregulation of plant m is for +.>The period set of the peak period is T p ，t p For the moment of peak value, the total number of peak periods is n 1 The output set of the peak period is P p The method comprises the steps of carrying out a first treatment on the surface of the The period set of the flat period is T f The total number of flat time periods is n 2 The output set of the flat period is P f The method comprises the steps of carrying out a first treatment on the surface of the The period set of valley period is T v The total number of time periods is n 3 The output set of valley period is P v ；/>The minimum peak shaver is compensated for a lower limit of time.
The m power station scheduling plan is generated as follows:
a. maximum peak time duration at m power stationsStep b is skipped when the step is performed; when->And (c) skipping to the step (c).
b. According to the daily planned power generation of m power stationsThe m power stations generate power uniformly, and the output of each period of the m power stations is +.>Δt is the period length, step k.
c. Setting the output of the m power station in each periodStep d is skipped.
d. Step e is skipped without distinguishing the early and late peak periods; with distinct early-late peak period discrimination, step f is skipped.
e. The hydro-power compensates the peak period output. The daily peak-adjustable electric quantity of the power stationPeak-regulating optimizing electric quantity E as power station opt . At t p For the center, in->The output of the peak period is increased to two sides by the unit, and then the following formula is adopted:
wherein:maximum output of hydropower for peak period; l is the hydropower energy>Compensating for a maximum number of peak periods; []Is a rounding function; ΔE represents hydropower->Compensating the residual peak regulating electric quantity after the force is output in the period of l time; />And the peak shaving output which can be compensated by the residual peak shaving electric quantity is shown. The output at peak time period is:
wherein: e (E) res And the residual adjustable peak power. When E is res When=0, step k is skipped; when E is res At > 0, step i is skipped.
f. Step g is skipped when the force output in the early peak period is compensated preferentially; and (3) when the output in the late peak period is compensated preferentially, skipping to the step (h).
g. Hydropower compensation early peak period output. Inputting the residual adjustable peak electric quantity or the daily adjustable peak electric quantity of the early peak period as the optimized electric quantity, and calculating the output set and the residual electric quantity E of the early peak period according to the formula of the step E res . E when the residual adjustable peak power is input res When=0, step l is skipped; when E is res When the value is more than 0, jumping to the step j; when the daily peak-adjustable electric quantity is input, E res When=0, step l is skipped; e (E) res And when the value is more than 0, skipping the step h.
h. Hydropower compensates for late peak period output. Inputting the residual adjustable peak electric quantity or the daily adjustable peak electric quantity in the late peak period as the optimized electric quantity, and calculating the output set and the residual electric quantity E in the late peak period according to the formula of the step E res . E when the residual adjustable peak power is input res When=0, jump to step l, E res When the value is more than 0, jumping to the step j; when the daily peak-adjustable electric quantity is input, E res When=0, step l is skipped; e (E) res At > 0, step g is skipped.
i. And (3) balancing the power output of the compensation early and late peak period by water and electricity, compensating the optimized electric quantity for the early and late peak period, enabling the power to generate electricity uniformly, and jumping to the step j if the remained optimized electric quantity exists.
j. The hydro-power compensates for the output of the plateau period. And taking the input residual adjustable peak electric quantity as an optimized electric quantity, and compensating the normal period according to the principle that the closer to the peak value, the more the compensation is performed.
E, calculating the formula to obtain the maximum peak shaving output in the flat periodResidual peak shaving force->The maximum compensation normal time quantity l is that the output of the normal time is:
when E is res When=0, step k is skipped; when E is res When > 0, step j is skipped.
k. The water and electricity compensates the output of the valley period. The input residual adjustable peak electric quantity is used as the optimized electric quantity of the water and electricity, and the output of the water and electricity valley period is calculated by adopting a uniform power generation mode, and the following formula is adopted:
step l is skipped.
Output power station m output process P m 。
Step3.4: and repeating step3.3 for a plurality of times, and outputting all power generation plans of the power station with the regulation capability.
The invention has the beneficial effects that:
firstly, the invention provides a flow for generating a hydropower dispatching scheme according to the matching characteristics of wind power output and load and the peak shaving capacity of hydropower. The main flow is as follows: (1) Based on the index of the degree of matching of the wind power output and the power grid load demand in time, whether the hydropower participates in the power grid peak shaving is flexibly adjusted according to the matching of the wind power output and the power grid load demand, and the risk of benefit loss caused by unnecessary peak shaving of the hydropower is reduced. (2) Based on the index of the matching degree of the wind power generation amount in the early-late peak period and the electric quantity required by the power grid, the electric quantity gap existing in the early-late peak period after the new energy is connected is considered, so that the scheduling rule of which period is preferentially compensated by the hydroelectric electric quantity is obtained, and the peak regulation capability of the hydropower is exerted to the maximum extent. (3) Based on the hydropower peak regulation capacity quantization method, factors such as forced output, ecological flow and the like of the power station are comprehensively considered, and the peak regulation capacity of the river basin steps is quantized. (4) And generating a hydropower scheduling plan by combining the hydropower quantity priority compensation rule and the quantized hydropower peak regulation capacity. Secondly, the invention takes the step hydropower in Fujian river basin as the background to carry out simulated scheduling. The application example results show that the method can fully consider the matching characteristics of the source load, and excavate and quantify the peak shaving capacity of the hydropower station. The generated scheduling plan is strong in interpretation and high in calculation speed, and has important reference significance for hydropower scheduling personnel to make a hydropower generation plan.
Drawings
FIG. 1 is a general framework of the method of the present invention;
FIG. 2 is a graph of typical daily peak-to-valley time period divisions in an embodiment;
FIG. 3 is a typical daily hydropower schedule plan in an embodiment.
Detailed Description
The invention is further described below with reference to the drawings and examples.
The method of the invention is now examined against the background of Fujian river basin. The coastal water resource of China in Fujian province is one of the provinces with rich water resource accumulation in China, the total water resource is 1168.7 hundred million cubic meters, the total water resource accounts for 4.2 percent of the total water resource of China, the Fujian province also has rich offshore wind energy resources, the wind energy resource accumulation within 20 meters in the coast is 2749 kilowatts, the wind energy resource with the water depth of 20-50 meters is 9530 kilowatts, and the offshore wind energy resource is about 5000 tens of thousands. Therefore, the new energy industry of the Fujian has huge development potential, but with the annual increase of wind power installation, the anti-peak shaving characteristic of wind power brings great challenges to the safe and stable operation of a power grid. How to fully excavate and quantify the peak shaving capacity of hydropower under the premise of considering the matching characteristics of wind power output and load and maintain the safe and stable operation of a power grid is a current problem to be solved urgently. According to the invention, the matching characteristics of wind power and load are analyzed by relying on practical operation data of the Minjian river basin step power station 2021, the peak regulation capacity of the river basin steps is quantized, and a scheduling plan is generated to verify the effectiveness of the model. Taking seasonal characteristics of wind power and incoming water into consideration, 2021 is divided into four quarters, and a typical scene of each quarter is selected according to matching indexes of wind power output and load to carry out simulated scheduling.
Step1: the valley period, the early peak period, the late peak period and the flat period are divided according to the fuzzy membership function and experience, see fig. 2, and the force matching index and the electric quantity matching index are calculated, and table 1 shows the force matching index and the electric quantity matching index of four typical days.
TABLE 1 typical daily wind power and load matching index table
| Index (I) | First quarter of | Second quarter of | Third quarter | Fourth quarter of |
| Force matchingIndex number | 1.21 | 1.21 | 1.26 | 1.23 |
| Electric quantity matching index | 0.58 | 0.36 | - | 0.40 |
Step2: watershed step power quantization
And (3) quantitatively analyzing the peak regulation capacity of the step power station in the Minjiang river basin according to the formula in the step (2), wherein the result is shown in Table 2.
Table 2 peak shaving capacity table for typical daily power station
Step3: generation of hydropower scheduling schemes
And guiding to generate a hydropower station scheduling plan based on the matching characteristics of wind power and system load and the quantification index of the hydropower station peak regulation capacity. Where δ=0.1 and ε=0.1, the scheduling results of the power station generated according to step (3) are shown in fig. 3. As can be seen from fig. 3, the method provided by the invention can consider the matching characteristics of wind power and load, and fully excavate and quantify the peak shaving capacity of the hydropower. The generated scheduling plan is strong in interpretation and high in calculation speed, and has important reference significance for hydropower scheduling personnel to make a hydropower generation plan.
Claims (1)
1. The hydropower peak regulation flexibility quantification and scheduling method is characterized by comprising the following steps of:
(1) Peak-valley matching characteristic analysis of wind power output and system load
1) Power grid load characteristic analysis
Step1.1.1: preliminary peak-to-valley period identification based on fuzzy membership function
Carrying out preliminary identification and division on peak-valley time periods of the load by adopting a fuzzy membership function; assume that a 96-point-a-day load value sequence is l= { L 1 ,…,L t …,L T Using a larger semi-trapezoid membership function to determine the probability P (L) that each period is a peak period on the load curve t ) The method comprises the steps of carrying out a first treatment on the surface of the Determining the probability V (L) that the load of each period is a valley period by adopting a semi-trapezoid membership function with smaller size t ) The calculation formula is as follows:
wherein: l (L) t Load value of the system for t period; l (L) max Is the maximum value of the system load on the same day; l (L) min Is the minimum value of the system load; t (T) all A set of time periods within one scheduling period; m is the total number of time periods in the scheduling period;
assume that the threshold values of the membership functions of the peak-valley periods are alpha respectively 1 And alpha 2 The sets of peak-to-valley periods are respectively T peak ,T valley ,T flat The number of elements in the peak-to-valley set is m respectively 1 ，m 2 ，m 3 The formula is shown below;
step1.1.2: correcting the peak-valley period identified by the fuzzy membership function based on the peak-valley period of the historical actual load data of the power grid, and dividing the valley period, the early peak period, the late peak period and the peaked period;
2) Wind power output and load matching analysis
Step1.2.1: and calculating the matching of wind power output and load according to the following formula:
wherein: pw (pw) t Wind power output in t period, MW; l (L) t The system load of the power grid in the t period is MW; NL (NL) t Removing net load after wind power for t-period power grid load, MW;peak-valley difference, MW, of system load in a scheduling period T;peak-to-valley difference, MW, of the payload in the scheduling period; zeta type toy p The method comprises the steps of measuring indexes of matching degree of wind power output and power grid load;
step1.2.2: according to the historical actual wind power output data and the power grid load data, calculating the matching degree xi of the wind power output and the power grid load according to Step1.2.1 p All xi p Sequencing the accumulated frequencies to determine a coefficient delta;
wherein: delta is the output matching coefficient threshold value of wind power output and load which are rated according to historical data, and the meaning of the expression is that the expression is delta p When the wind power is more than or equal to 1+delta, the wind power is reversely subjected to peak shaving, the peak shaving capacity requirement of the power grid is larger, and the power supply of the power grid is required to participate in peak shaving at the moment; 1-delta < xi p When the wind power is less than 1+delta, the wind power has no influence on the peak shaving capacity requirement of the power grid, and the peak shaving of the power grid water supply is not needed at the moment; when xi p When the wind power is less than or equal to 1-delta, the wind power is in positive peak regulation, and the peak regulation required capacity of the power grid is reduced;
3) Matching degree analysis of peak-valley period electric quantity distribution
According to the dividing result of the peak-valley period in the step 1), analyzing the matching degree of the wind power generation amount of the early peak period and the late peak period and the required electric quantity of the power grid to obtain a compensation rule of the water power and the electric quantity;
step1.3.1: calculating the matching degree of the wind power generation amount in the early-late peak period and the power grid required electric quantity according to the following steps:
wherein: LE (LE) p1 、LE p2 The power requirements of the early peak period and the late peak period are respectively represented, and MWh is measured; WE (Power of industry) p1 、WE p2 The method comprises the steps of respectively representing wind power generation capacity of an early peak period and wind power generation capacity of a late peak period, and MWh; zeta type toy E The matching degree of the wind power generation amount and the power grid required electric quantity in the early-late peak period is represented;
step1.3.2: according to the historical actual wind power output data and grid load data, calculating the matching degree xi of the wind power generation amount in the early-late peak period and the grid required electric quantity according to the Step1.3.1 E All xi E Sequencing the accumulated frequencies to determine a coefficient epsilon;
wherein: epsilon is the electric quantity matching coefficient threshold value of wind power output and load which are rated according to historical data, and the meaning of the expression is that the expression is delta E2 When the electric quantity is more than or equal to 1+epsilon, the water-electricity priority compensation early peak electric quantity requirement; when xi E2 When the electricity quantity is less than or equal to 1-epsilon, the water electricity preferentially compensates the late peak electricity quantity; when 1-epsilon is less than or equal to zeta E2 When less than or equal to 1+epsilon, the hydropower balance compensates the electric quantity demand of the early and late peaks;
(2) Quantification of drainage basin step peak regulation capability
The peak shaving capacity of the hydropower station is quantified as follows:
wherein: eta is the daily average water consumption rate of the power station, m 3 /kW·h；qp eco For the ecological flow of the power station, m 3 /s；Forced output MW of the power station; qp (q) max For maximum power generation flow of power station, m 3 /s；/>Is the installed capacity, MW, of the power station; />The power station is the daily minimum output, MW; />The power station is the daily maximum output, MW;
the calculation formulas of the daily peak regulation capacity of the power station, the daily adjustable peak capacity of the power station and the maximum peak duration of the power station are as follows:
wherein:peak regulating capacity, MW, of a power station; />Planning power generation capacity and MWh for the current day of the power station; Δt is the length of the period; />H is the maximum peak duration of the power station;
(3) Generation of hydropower scheduling schemes
Guiding to generate a hydropower station scheduling plan based on the matching characteristics of the wind power and the system load in the step (1) and the quantitative index of the hydropower peak shaving capacity in the step (2);
step3.1: analyzing the peak-valley matching characteristics of wind power output and system load, and judging whether water power peak regulation and a compensation rule of the water power peak regulation are needed or not;
step3.2: quantifying peak regulation capacity of river basin steps, and calculating daily peak regulation capacity of power station with regulation capacityDaily peak-adjustable electric quantity +.>Maximum peak duration->Daily minimum output of power station->And the daily planned power generation of the power station->
Step3.3: generating a scheduling plan of a power station with the capability of adjusting; assuming that the set of time periods in the scheduling period is T, the total number of the time periods is n, and the sunrise power set of the power station m is P m Up-regulation of plant m is used asThe downregulation of plant m is for +.>The period set of the peak period is T p ，t p For the moment of peak value, the total number of peak periods is n 1 The output set of the peak period is P p The method comprises the steps of carrying out a first treatment on the surface of the The period set of the flat period is T f The total number of flat time periods is n 2 The output set of the flat period is P f The method comprises the steps of carrying out a first treatment on the surface of the The period set of valley period is T v Total number of time periodsIs n 3 The output set of valley period is P v ；/>The minimum peak shaving compensation time lower limit;
the m power station scheduling plan is generated as follows:
a. maximum peak time duration at m power stationsStep b is skipped when the step is performed; when->Step c is skipped when the step is performed;
b. according to the daily planned power generation of m power stationsThe m power stations generate power uniformly, and the output of each period of the m power stations isΔt is the period length, step k;
c. setting the output of the m power station in each periodStep d, jumping to the step;
d. step e is skipped without distinguishing the early and late peak periods; f, jumping to the step f, wherein the distinguishing of the early and late peak time periods is obvious;
e. hydro-power compensation peak period output: the daily peak-adjustable electric quantity of the power stationPeak-regulating optimizing electric quantity E as power station opt The method comprises the steps of carrying out a first treatment on the surface of the At t p For the center, in->Is a single sheetThe output of the bit increasing peak period to both sides respectively has the following formula:
wherein:maximum output of hydropower for peak period; l is the hydropower energy>Compensating for a maximum number of peak periods; []Is a rounding function; ΔE represents hydropower->Compensating the residual peak regulating electric quantity after the force is output in the period of l time; />The peak shaving output which can compensate the residual peak shaving electric quantity is represented; the output at peak time period is:
wherein: e (E) res The residual adjustable peak power is; when E is res When=0, step k is skipped; when E is res When the value is more than 0, jumping to the step i;
f. step g is skipped when the force output in the early peak period is compensated preferentially; when the output in the late peak period is compensated preferentially, the step h is skipped;
g. hydropower compensation early peak period output: inputting the residual adjustable peak electric quantity or the daily adjustable peak electric quantity of the early peak period as the optimized electric quantity, and calculating the output set and the residual electric quantity E of the early peak period according to the formula of the step E res The method comprises the steps of carrying out a first treatment on the surface of the E when the residual adjustable peak power is input res When=0, step l is skipped; when E is res When the value is more than 0, jumping to the step j;when the daily peak-adjustable electric quantity is input, E res When=0, step l is skipped; e (E) res When the value is more than 0, skipping to the step h;
h. hydropower compensation late peak period output: inputting the residual adjustable peak electric quantity or the daily adjustable peak electric quantity in the late peak period as the optimized electric quantity, and calculating the output set and the residual electric quantity E in the late peak period according to the formula of the step E res The method comprises the steps of carrying out a first treatment on the surface of the E when the residual adjustable peak power is input res When=0, jump to step l, E res When the value is more than 0, jumping to the step j; when the daily peak-adjustable electric quantity is input, E res When=0, step l is skipped; e (E) res When the value is more than 0, the step g is skipped;
i. the water and electricity balance compensates the output force of the early and late peak period, the optimized electric quantity compensates the early and late peak period, so that the power is uniformly generated, and if the rest optimized electric quantity exists, the step j is skipped;
j. the output of the hydroelectric compensation flat period: taking the input residual adjustable peak electric quantity as an optimized electric quantity, and compensating the normal period according to the principle that the closer to the peak value, the more the compensation is performed;
e, calculating the formula to obtain the maximum peak shaving output in the flat periodResidual peak shaving force->The maximum compensation normal time quantity l is that the output of the normal time is:
when E is res When=0, step k is skipped; when E is res When the value is more than 0, jumping to the step j;
k. the water and electricity compensate the output of the valley period; the input residual adjustable peak electric quantity is used as the optimized electric quantity of the water and electricity, and the output of the water and electricity valley period is calculated by adopting a uniform power generation mode, and the following formula is adopted:
step l is skipped;
output power station m output process P m ；
Step3.4: and repeating step3.3 for a plurality of times, and outputting all power generation plans of the power station with the regulation capability.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310489833.8A CN116544951A (en) | 2023-05-04 | 2023-05-04 | Hydropower peak regulation flexibility quantification and scheduling method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310489833.8A CN116544951A (en) | 2023-05-04 | 2023-05-04 | Hydropower peak regulation flexibility quantification and scheduling method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116544951A true CN116544951A (en) | 2023-08-04 |
Family
ID=87446420
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310489833.8A Pending CN116544951A (en) | 2023-05-04 | 2023-05-04 | Hydropower peak regulation flexibility quantification and scheduling method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116544951A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116823000A (en) * | 2023-08-31 | 2023-09-29 | 华能澜沧江水电股份有限公司 | Hydropower compensation peak regulation analysis and evaluation method and device thereof |
-
2023
- 2023-05-04 CN CN202310489833.8A patent/CN116544951A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116823000A (en) * | 2023-08-31 | 2023-09-29 | 华能澜沧江水电股份有限公司 | Hydropower compensation peak regulation analysis and evaluation method and device thereof |
| CN116823000B (en) * | 2023-08-31 | 2024-01-19 | 华能澜沧江水电股份有限公司 | Hydropower compensation peak regulation analysis and evaluation method and device thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6736112B2 (en) | A short-term practical scheduling method for ultra-large-scale hydropower stations | |
| Lu et al. | Optimization model for the short-term joint operation of a grid-connected wind-photovoltaic-hydro hybrid energy system with cascade hydropower plants | |
| CN110717688B (en) | Water, wind and light short-term combined optimization scheduling method considering new energy output uncertainty | |
| Yuan et al. | Stochastic optimization model for the short-term joint operation of photovoltaic power and hydropower plants based on chance-constrained programming | |
| CN107153885B (en) | Real-time power generation plan optimization method considering deep peak shaving of thermal power generating unit | |
| CN112163700B (en) | Electrochemical energy storage power station planning method considering cycle life of energy storage battery | |
| CN110620397B (en) | Peak regulation balance evaluation method for high-proportion renewable energy power system | |
| CN114243794B (en) | Wind, light and water multi-energy complementary system flexibility requirement quantification and coordination optimization method | |
| CN116544951A (en) | Hydropower peak regulation flexibility quantification and scheduling method | |
| CN114996908B (en) | Active power distribution network expansion planning method and system considering intelligent soft switch access | |
| Feng et al. | Optimal allocation of hydropower and hybrid electricity injected from inter-regional transmission lines among multiple receiving-end power grids in China | |
| Zhang et al. | Assessing the integration potential of new energy in river basin clean energy corridors considering energy-power coupled complementary operation modes | |
| CN104636824A (en) | Distributed photovoltaic siting and sizing method for determining minimum permeability | |
| CN105305463B (en) | The idle work optimization method based on probabilistic loadflow of meter and photovoltaic generation and harmonic pollution | |
| CN112713615B (en) | Quick coordination scheduling method and system for electricity-gas integrated energy system | |
| CN113255982A (en) | Medium-long term optimized scheduling method for wind-light-water complementary system | |
| CN106355297A (en) | Electrolytic aluminum load characteristic-based power grid loss reduction optimization method | |
| Jing et al. | Benefit compensation of hydropower-wind-photovoltaic complementary operation in the large clean energy base | |
| CN112994087B (en) | Multi-source power system medium-term optimization scheduling method based on conditional risk constraint | |
| Cheng et al. | Analysis of multi-scenario power supply and demand balance in Shandong power grid based on the new generation PSDB platform | |
| CN110580368A (en) | heat supply unit power generation plan compilation method taking peak regulation capacity maximization as target | |
| CN113131514B (en) | Multi-source active control method and system | |
| CN113922398B (en) | Power distribution method for optical storage station under multi-application scene | |
| Wu et al. | Optimal operation of multi-objective hydropower reservoir with ecology consideration | |
| CN117810999A (en) | Source-network-load-extraction-storage coordination extension planning method considering direct current output requirements |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |