CN116402319B - Multi-round electricity limiting oriented ordered electricity utilization automatic programming method, medium and equipment - Google Patents
Multi-round electricity limiting oriented ordered electricity utilization automatic programming method, medium and equipment Download PDFInfo
- Publication number
- CN116402319B CN116402319B CN202310671259.8A CN202310671259A CN116402319B CN 116402319 B CN116402319 B CN 116402319B CN 202310671259 A CN202310671259 A CN 202310671259A CN 116402319 B CN116402319 B CN 116402319B
- Authority
- CN
- China
- Prior art keywords
- limiting
- electricity
- users
- user
- round
- 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.)
- Active
Links
- 230000000670 limiting effect Effects 0.000 title claims abstract description 202
- 230000005611 electricity Effects 0.000 title claims abstract description 181
- 238000000034 method Methods 0.000 title claims abstract description 33
- 230000006870 function Effects 0.000 claims description 20
- 238000004422 calculation algorithm Methods 0.000 claims description 10
- 238000004590 computer program Methods 0.000 claims description 9
- 238000010924 continuous production Methods 0.000 claims description 5
- 238000003860 storage Methods 0.000 claims description 4
- 230000002829 reductive effect Effects 0.000 abstract description 5
- 230000002354 daily effect Effects 0.000 description 15
- 238000004519 manufacturing process Methods 0.000 description 10
- 238000004364 calculation method Methods 0.000 description 7
- 238000012163 sequencing technique Methods 0.000 description 4
- 238000005457 optimization Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000036961 partial effect Effects 0.000 description 2
- 230000003442 weekly effect Effects 0.000 description 2
- 230000002411 adverse Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008094 contradictory effect Effects 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000005684 electric field Effects 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 230000003203 everyday effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000011144 upstream manufacturing Methods 0.000 description 1
Classifications
-
- 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
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
-
- 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
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- 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
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/04—Constraint-based CAD
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/04—Power grid distribution networks
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Economics (AREA)
- Physics & Mathematics (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Computation (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Development Economics (AREA)
- Health & Medical Sciences (AREA)
- Educational Administration (AREA)
- Data Mining & Analysis (AREA)
- Game Theory and Decision Science (AREA)
- Public Health (AREA)
- Computer Hardware Design (AREA)
- Primary Health Care (AREA)
- Geometry (AREA)
- General Health & Medical Sciences (AREA)
- Water Supply & Treatment (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Biology (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a multi-round electricity limiting oriented orderly electricity utilization automatic programming method, medium and equipment, and relates to the technical field of electricity. According to the obtained user information, the users are divided into a first class of users and a second class of users, an objective function is built by taking the sum of the electricity limiting load values of the users to be minimum and the difference of the electricity limiting proportion of the first class of users and the electricity limiting proportion of the second class of users to be minimum as a target, complete constraint conditions are built by combining the electricity limiting indexes of each round and the upper limit of the electricity limiting proportion, and a multi-round electricity limiting scheme is output through multi-round solving, so that the fairness of the ordered electricity using scheme is improved, the loss of electricity limiting to the users is reduced, and the efficiency of the ordered electricity using scheme is improved.
Description
Technical Field
The invention relates to the technical field of electricity, in particular to an automatic programming method, medium and equipment for orderly electricity utilization facing multi-round electricity limiting.
Background
The orderly power utilization refers to a method for limiting the power utilization requirements of partial users under the conditions of insufficient power supply, accident emergency and the like so as to realize safe and stable operation of a power grid and maintain stable and orderly power supply level. When the power supply and demand are contradictory, a series of measures such as peak staggering, peak avoiding, power limiting and the like are adopted to standardize the power utilization order, so that the unplanned switching-out power limiting is avoided, and the adverse effects on society and users caused by insufficient power supply are reduced to the minimum.
At present, the orderly power utilization scheme is mainly compiled by manual mode, so that not only is the efficiency quite low, but also the requirements of a large number of users and various electricity limiting constraints are difficult to consider. Particularly, under the condition of multiple rounds of electricity limiting, the scheme provided by the manual programming mode is high in subjectivity, and lacks of fairness consideration, and enterprise load production characteristics and industry internal linkage effect are not considered.
Disclosure of Invention
In order to solve at least one technical problem mentioned in the background art, the invention aims to provide an automatic orderly power utilization programming method for multi-round power limiting so as to improve the fairness of orderly power utilization scheme programming, reduce the loss of power limiting to users and improve the programming efficiency of orderly power utilization schemes.
In order to achieve the above purpose, the present invention provides the following technical solutions:
in a first aspect, an embodiment of the present invention provides a method for automatically programming orderly power consumption for multi-round power limiting, including:
acquiring user information of a plurality of users, wherein the user information is used for representing the electricity utilization characteristics of the users, the users are classified into a first type user and a second type user according to whether the users are continuous production type, if yes, the users are the first type user, and if not, the users are the second type user;
constructing an objective function by taking the minimum sum of the electricity limiting load values of the plurality of users and the minimum difference of the electricity limiting proportion of the first type of users and the second type of users as targets;
determining constraint conditions matched with the objective function according to the user information, the limiting targets of all rounds and the upper limit value of the limiting proportion of all rounds, wherein the limiting targets of all rounds and the upper limit value of the limiting proportion of all rounds are preset values;
and carrying out multi-round solving on the objective function according to constraint conditions matched with the objective function and the user information to respectively obtain the electricity limiting load values of the users in each round of electricity limiting.
Further, the user information includes:
user number, user type, maximum allowable electricity limiting load value, electricity usage level, ranking weight, industry category.
Further, the objective function is:
，/>，/>；
wherein ,、/>respectively-> and />Weights of (2); />An actual daily electricity limiting load value for a first class of users m of the kth electricity utilization level of the s-th round; />For the kth power consumption level of the s-th wheelAn actual electricity limiting load value of the second class user n on the t-th day in one period; />、/>The electricity limiting proportion of the first class of users and the second class of users of the current power utilization level of the kth round is respectively; />Is the sum of the limit load values of the several users, < >>A difference between the electricity limiting ratios for the first type of users and the second type of users; t is the number of days of a cycle; k is the number of electricity utilization levels; />The number of first class users for the kth power usage level; />The number of the second class of users for the kth power utilization level; s is the power limiting round.
Further, the determining the constraint condition matched with the objective function according to the user information, the limit electric targets and the limit electric proportion upper limit value of each round includes:
distributing corresponding electricity limiting priority according to the sorting weight of the user, and determining an electricity limiting sequence constraint condition; wherein, the larger the sorting weight is, the higher the electricity limiting priority is;
determining a cross-wheel association constraint condition according to the limiting proportion of the user in the previous-wheel limiting and the upper limit value of the limiting proportion of each wheel; wherein, the limiting proportion of the user on the current wheel is larger than or equal to the limiting proportion of the previous wheel and smaller than or equal to the upper limit value of the limiting proportion of the current wheel;
determining a limit electric level constraint condition according to the electric level of the user; wherein, the electricity limiting proportion of the users with low electricity consumption level is smaller than or equal to the electricity limiting proportion of the users with high electricity consumption level;
determining a first-class user electricity limiting constraint condition according to the maximum allowable electricity limiting load value of the first-class user;
determining a second class user electricity limiting constraint condition according to the maximum allowable electricity limiting load value of the second class user;
determining a limiting index constraint condition according to the lowest limiting load value; wherein the lowest daily electrical load value is a preset value;
determining industry insurance constraint conditions according to the total number of users in the same industry in the second class of users; wherein the number of users in the second class of users in the same industry with a limit electric power ratio greater than 0 is smaller than the total number of users in the industry;
determining continuous stop constraint conditions according to the current wheel limiting proportion of the second class user;
and determining fairness constraint conditions according to the electricity utilization level of the user and the electricity limiting targets of each round.
Further, the number of the electricity consumption levels is 5, and the electricity consumption levels are sequentially increased from the 1 st level to the 5 th level corresponding to the electricity limiting proportion.
Further, the limit electrical rotation s is greater than 1.
Further, the algorithm of multi-round solving is a branch-and-bound algorithm, and the output of the previous round is used as the input of the next round.
In a second aspect, embodiments of the present invention also provide a computer storage medium having stored thereon a computer program which, when executed by a processor, implements any of the multiple-round electricity-limiting oriented orderly electricity utilization automatic programming methods described above.
In a third aspect, an embodiment of the present invention further provides a terminal device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor implements any of the orderly power consumption automatic programming methods facing multiple rounds of power limiting as described above when executing the computer program.
Compared with the prior art, the invention has the beneficial effects that: according to the obtained user information, the users are divided into a first class of users and a second class of users, an objective function is built by taking the sum of the electricity limiting load values of the users to be minimum and the difference of the electricity limiting proportion of the first class of users and the electricity limiting proportion of the second class of users to be minimum as a target, complete constraint conditions are built by combining the electricity limiting indexes of each round and the upper limit of the electricity limiting proportion, and a multi-round electricity limiting scheme is output through multi-round solving, so that the fairness of the ordered electricity using scheme is improved, the loss of electricity limiting to the users is reduced, and the efficiency of the ordered electricity using scheme is improved.
Drawings
FIG. 1 is a flowchart of an automatic programming method for orderly power consumption for multi-round power limiting according to an embodiment of the present invention;
FIG. 2 is a flow chart of a multi-round solution provided by an embodiment of the present invention;
FIG. 3 is a bar graph of the A-F wheel limit indicators and the actual limit loads of each wheel provided by the embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to solve the above problems in the prior art, the embodiment of the invention discloses a method for programming an orderly power consumption scheme for limiting electricity in multiple rounds, and it should be noted that an execution subject of the embodiment of the invention may be a computer or any electronic device with data processing capability. For convenience of description, the following details will be respectively described with the electronic device as an execution body.
Embodiment one:
as shown in fig. 1, fig. 1 is a flowchart of an automatic programming method for orderly power consumption for multi-round power limiting according to an embodiment of the present invention.
Step S101, user information of a plurality of users is obtained, wherein the user information is used for representing the electricity utilization characteristics of the users, the users are divided into a first type user and a second type user according to whether the users are continuous production types, if yes, the users are the first type users, and if not, the users are the second type users.
The electronic device obtains user information of all users in a certain area from the database, and the area can be a province, a city, a county, or an artificially divided district, and the users can be enterprises or general people, which is not limited by the embodiment of the invention. The user information is used for representing the electricity utilization characteristics of the users, and is divided into a daily peak-avoiding user and a Zhou Cuobi peak user according to whether the users are continuous production types. The continuous production type users refer to users who have to arrange production tasks every day in one period and cannot completely stop power supply and production, namely first type users, namely users who avoid peak by day; discontinuous production type users refer to users who allow production tasks to be interrupted for a few days in one period and have complete power failure, namely second type users, also called Zhou Cuobi peak users.
In one embodiment, the user information includes: user number, user type, maximum allowable electricity limiting load value, electricity usage level, ranking weight, industry category.
The user in the embodiment of the invention can be an enterprise user, and the electronic equipment acquires the user files (such as user numbers, user names and the like), user types, reference loads, security loads, maneuvering loads, electricity utilization levels, sequencing weights, industry types, continuous stop marks and other information of each enterprise from the database. The user types comprise the daily peak-shifting avoidance users and Zhou Cuobi peak users; the reference load is a load reference value of each period obtained through calculation and analysis according to the power load characteristics of the user and the historical power data, and is used for reflecting the basic power consumption condition of the user; the security load is the electric load required for guaranteeing the personal and property security of the electric field station; the maneuvering load refers to the load of the user of the maneuvering load when the emergency gap occurs in the power grid and the pressure of the user of the maneuvering load is reduced to be in place within 20 minutes; the continuous stop sign refers to a sign whether a user allows continuous power failure; the maximum allowable limit load value is equal to the difference value obtained by subtracting the dynamic load from the reference load and subtracting the safety load, and if the difference value is negative, the value is 0. In addition, the user information may be other data, which is not particularly limited in the embodiment of the present invention.
In one embodiment, the number of user levels is 5, and the power consumption levels sequentially increase from level 1 to level 5. Specifically, the user classes of five types, which are necessary guarantee (i.e., white list users, not participating in electricity limitation), priority guarantee, general limitation, and key limitation, can be classified.
Step S102, an objective function is constructed with the aim of minimizing the sum of the power limiting load values of a plurality of users and minimizing the difference between the power limiting ratios of the first class of users and the second class of users.
In one embodiment, the objective function is:
，/>，/>；
wherein ,、/>respectively-> and />Weights of (2); />An actual daily electricity limiting load value for a first class of users m of the kth electricity utilization level of the s-th round; />The actual electricity limiting load value of the second class user n of the kth electricity utilization level of the s-th round in the t-th day in one period; />、/>The electricity limiting proportion of the first class of users and the second class of users of the current power utilization level of the kth round is respectively; />Is the sum of the limit load values of the several users, < >>A difference between the electricity limiting ratios for the first type of users and the second type of users; t is the number of days of a cycle; k is the number of electricity utilization levels; />The number of first class users for the kth power usage level; />The number of the second class of users for the kth power utilization level; s is the electricity limiting round, and the electricity limiting round s is more than 1, and represents multi-round electricity limiting. For convenience of description, the above one period T takes one week, i.e., t=7.
On the premise that the maximum allowable limit load value is satisfied, the actual limit load value is usedDifference between actual limit ratio of minimum sum day peak-avoiding user and Zhou Cuobi peak user +.>The smaller the minimum is the optimization target, the closer the Zhou Cuobi peak user power limit ratio is to the daily peak-avoiding user power limit ratio, which indicates that the two types of users are affected by the power failure to be nearly the same, and the fairer the two types of users are.
Step S103, determining constraint conditions matched with the objective function according to the user information, the limiting targets and the limiting proportion upper limit values of all rounds, wherein the limiting targets and the limiting proportion upper limit values of all rounds are preset values.
The upper limit electric power target and the upper limit electric power proportion limit value of each turn are preset, and specifically, as shown in table 1, table 1 provides the upper limit electric power proportion limit value of each turn of the power consumption level user.
TABLE 1 upper limit of the ratio of different rounds of power limits for each level of users
In table 1, the limit frequency s is six, and is a to F, and the limit ratio of each user should not exceed the value in table 1.
In one embodiment, step S103 may be subdivided into the following steps:
step S1031, distributing corresponding electricity limiting priority according to the sorting weight of the user, and determining the constraint condition of the electricity limiting sequence; wherein, the larger the sorting weight is, the higher the limit electric priority is.
On the principle of large-weight enterprise priority limit, if enterprise users with small weight participate in limit electricity, users with higher weight must limit electricity too. Let the weight of the ith user of the kth class of the s-th round beIf the ranking weight of a user j of the first level satisfies +.>There is->, in the formula ,/>A variable of 0-1 represents whether the ith user of the kth level of the s-th round participates in orderly power utilization, wherein 1 is taken to represent participation, and 0 is taken to represent non-participation; the larger the electricity limiting sequencing weight is, the priority arrangement electricity limiting is indicated, and the value of the electricity limiting sequencing weight is determined by factors such as industry category, electricity consumption level, energy consumption level and the like of the user.
Step S1032, determining a cross-wheel association constraint condition according to the limiting proportion of the user in the previous-wheel limiting and the upper limit value of the limiting proportion of each wheel; the limiting proportion of the user on the current wheel is larger than or equal to the limiting proportion of the previous wheel and smaller than or equal to the upper limit value of the limiting proportion of the current wheel.
The k-th class user i (comprising the peak-shifting user m and the peak-shifting user n Zhou Cuobi) participates in the electricity limiting, the user must participate in the next round, and the electricity limiting proportion of the users in the next round is not lower than the electricity limiting proportion of the previous round, and the upper limit requirement of the electricity limiting proportion in the table 1 is met at the same time, namely，/>，/>，；
in the formula ,for the (s-1) th round, whether the kth level user i is involved in the limit situation, for the s-th round +.>Is of known value, in particular +.when s=1>Taking 0; />、/>The power limit ratios of the k-rank daily peak-shifting users and Zhou Cuobi peak users of the previous round, i.e., (s-1), respectively, are known values for both rounds s and +.>；/>、/>The upper limit ratio limit value of the corresponding round and the user type in the table 1; />、/>The current limiting ratios of the users of the current s-th round and the k-th round are respectively the peak shifting and Zhou Cuobi peak, and the attention is paid to the +.>And->Represents the k-th level instead of the limiting proportion of a certain user, the limiting proportion of a single user is defined by +.>And->Or->And->Determining together; />The variable is 0-1, which represents whether the user n of the kth level cycle peak-staggering avoidance of the s-th round participates in the electricity limiting variable on the t-th day, if so, taking 1, otherwise, taking 0; />The user n participates in the electricity limiting situation for the kth level cycle staggering peak of the previous round, namely (s-1), and the value is known for the (s-1) th round; />Indicating that user n is limited on the t-th day and the user is on the next round (i.e. s round)Electricity must be limited on day t (power cut off on the same day as the wheel).
Step S1033, determining a limit level constraint condition according to the power utilization level of the user; wherein, the electricity limiting proportion of the users with low electricity consumption level is smaller than or equal to the electricity limiting proportion of the users with high electricity consumption level.
The user-limit electric power proportion of the k-1 level is not higher than the user-limit electric power proportion of the k level, namely
，/>。
Step S1034, determining a first type user electricity limiting constraint condition according to the maximum allowable electricity limiting load value of the first type user.
The actual limiting load of the user who avoids peak with time can be expressed as
；
in the formula ,for the actual daily limit load variable of the kth-class daily peak-shifting user m of the s-th round, it is shown that the daily peak-shifting user m participates in limit electricity (>) The ratio of the electricity limiting for 7 days in 1 week is the same; />The maximum allowable limit load value of the peak shifting user m is avoided for the kth level.
There is a nonlinear term in (variable +.>And variable->For ease of solution), the above equivalent is converted into the following linear form, i.e
，/>；
When (when)In the time, we know->The method comprises the steps of carrying out a first treatment on the surface of the When->In the time, we know->。
Step S1035, determining the second class user electricity limiting constraint condition according to the maximum allowable electricity limiting load value of the second class user.
The actual limiting load of the Zhou Cuobi peak user can be expressed as
； in the formula ,/>For the actual electricity limiting load variable of the kth-class week peak-shifting user n in the kth week, different from the day peak-shifting user, the week peak-shifting user allows discontinuous production, so that whether each day participates in electricity limiting can be different; />The maximum allowable limit load value of peak user n is avoided for the kth class period.
Power limiting ratio of Zhou Cuobi peak user nWhether to participate in the limit electric variable per day->The relationship between them can be expressed as +.>； in the formula ,/>The limiting proportion of the peak-shifting user n is avoided for the kth grade of the s-th round. The above formula means that the limiting ratio of the peri-peak avoidance users n is the ratio of the number of days of 1 week reference to the limiting ratio to the total number of days.
Power limiting ratio of Zhou Cuobi peak user nThe relation between the user's limit ratio with the whole k-th level cycle peak avoidance can be expressed as +.>The method comprises the steps of carrying out a first treatment on the surface of the The above equation shows that if the Zhou Cuobi peak user n participates in the s-th round of electricity limiting, the electricity limiting ratio must be equal to the common electricity limiting ratio of the entire k-th class of users to ensure fairness.
Taking into account thatFor quadratic term, for easy solution, the following linear relation is adopted for equivalent transformation:
，/>the method comprises the steps of carrying out a first treatment on the surface of the When->In the time, we know->The method comprises the steps of carrying out a first treatment on the surface of the When->In the time, we know->。
Step S1036, determining a limit electricity index constraint condition according to the lowest daily limit electricity load value; wherein the lowest daily electrical load value is a preset value.
The actual limit loads of the peak shifting user and the Zhou Cuobi peak user in each round of inner days need to meet the minimum limit electric index, namely； in the formula ,/>Is the total electricity limiting index of the t day; />Peak user number is avoided for the kth level; />Peak user number is misplaced for the kth class.
Step S1037, determining industry insurance constraint conditions according to the total number of users in the same industry in the second class of users; wherein the number of users in the second class of users in the same industry with a limit electric power ratio greater than 0 is less than the total number of users in the industry.
In order to reduce the influence of power failure on society, avoid the impact of the complete stop of a certain industry on the upstream and downstream of an industrial chain, for Zhou Cuobi peak users, the same round and the same industry do not allow the complete stop of a certain day, namely； in the formula ,/>Indicating whether the kth level user z within a certain line limits his/her power on the t th day of the s round,/for a certain line>Representing the user's limit; />Indicating that the user is not limited; z is the number of users in an industry.
Step S1038, determining continuous stop constraint conditions according to the current wheel limit proportion of the second class user.
For partial cycle peak avoidance users, for example, some industrial enterprises with inertia and continuity equipment cannot start and stop frequently in the production cycle of products, otherwise the production plan is influenced, and in order to reduce the influence of limit electricity on the production plan as much as possible, continuous limit electricity requirements should be considered, namely, users with limit electricity time of one week being longer than that of one day, the limit electricity time is continuous, namely；/>；/>；/>； in the formula ,the Zhou Cuobi peak user n is represented by a state switching variable of t days compared with the previous day, and the continuous power limiting requirement is met when the number of state switching (production stopping/running) is not more than 2.
Step S1039, determining fairness constraint conditions according to the electricity consumption level of the user and the electricity limiting targets of each round.
When the lowest limit proportion 1/7 cannot meet the limit target, the other users not participating in limit are preferably included in the limit scheme instead of increasing the limit proportion of the limited users to ensure the fairness of the participation of the users in limit, i.e
；
And combining all the constraint conditions to obtain the ordered limited electricity optimizing model. The above steps S1031 to S1039 do not indicate a sequential relationship, but the related constraint conditions need to be satisfied at the same time.
And step S104, carrying out multi-round solving on the objective function according to constraint conditions matched with the objective function and user information to respectively obtain the electricity limiting load values of a plurality of users in each round of electricity limiting.
In one embodiment, the algorithm for multiple round solution is a branch-and-bound algorithm, and multiple round solution takes the output of the previous round as the input of the next round. It is easy to know that solving the objective function is a mixed integer linear programming problem, and can be directly solved by adopting branch-and-bound or other optimizing tools, and the branch-and-bound algorithm is a common technical means for solving the linear programming problem, and the invention is not repeated here.
As shown in fig. 2, fig. 2 is a flowchart of a multi-round solution according to an embodiment of the present invention. Step S104, including:
(1) Initializing, calculating T, K, S according to the collected basic data,、/>Equivalent, let s=0, ++>,，/>，/>；
(2) s=s+1; and calculating the orderly power utilization scheme of the s-th round. Summing the user data, the upper limit of the ratio of the s-th round of electricity in Table 1Substituting into constraint conditions, adoptAnd solving by a branch-and-bound algorithm. If the solving is successful, the step (3) is carried out; if the solving fails, the step (4) is carried out;
(3) After the s-turn solution is successful, judging whether s=6 is satisfied, if not, obtaining the result of the turnAs the input of the next round of calculation, correspondingly updating the variables in the cross-round constraint conditions, and turning to the step (2), otherwise, outputting the A-F round electricity limiting schemes, and ending the program;
(4) The calculation failure information is printed and the program is terminated.
In order to facilitate understanding, the method of the present invention will be described below by taking a regional limit as an example. The process of obtaining the multi-round electricity limiting scheme by using the orderly electricity utilization automatic programming method facing multi-round electricity limiting provided by the embodiment I is as follows:
step S201, user information is acquired.
Taking a region as an example, a total of 1476 enterprises can participate in orderly power consumption, wherein the users of the peak-shifting user 21 and the peak-shifting user 1455 are in daily life. Information of electricity utilization level, reference load, security load, maneuvering load, user type, sequencing weight, continuous stop or not and the like of each enterprise is obtained through collecting and researching, and enterprise user data are shown in table 2.
Table 2 enterprise user data
The lowest limit indexes of each wheel A-F are 23971.40343, 48815.42857, 78733.58514, 131357.4237, 154460.5123 and 182541.3366 respectively.
Step S202, calculating a maximum allowable limit load value according to the data collection condition, wherein the calculation formula is as follows: maximum allowable limit load value = reference load-security load-maneuver load; k=5, t=7, s=6, m=21, n=1455 and s=0,，/>，/>，/>，k=1，2，…，5，i=1，2，…，1476。
step S203, s=s+1, summing the user data in S201, the upper limit of the a-wheel limit ratio for each level in table 1Substituting the power consumption constraint conditions to obtain a 1 st round (namely, round A) ordered power consumption optimization model, and then solving by adopting a branch and bound algorithm to obtain a round A (s=1) power limiting scheme of 1476 enterprises, wherein the power limiting scheme comprises 5 grades of power limiting proportion of all day peak-avoiding users and Zhou Cuobi peak users>、/>Whether each enterprise participates in the electricity limiting situation>The user who is weekly peak-avoiding is restricted by each day of the week>。
Step S204, s=s+1, the user data in S201, the upper limit of the B-round electricity limit ratio for each level in table 1, and the previous round (a-round) resultSubstituting the current limiting scheme into all constraint conditions to obtain a 2 nd round (namely a B round) ordered electricity utilization optimization model, and then solving by adopting a branch and bound algorithm to obtain a B round (s=2) electricity limiting scheme of 1476 enterprises, wherein the electricity limiting scheme comprises 5 grades of all-day peak-staggering users and Zhou Cuobi peak users>、/>Whether each enterprise participates in electricity limitingThe user who is weekly peak-avoiding is restricted by each day of the week>。
According to the procedures of step S203 and step S204, the electricity limiting schemes of the subsequent four wheels (i.e., C wheel, D wheel, E wheel, F wheel) are calculated. If a certain round of calculation is unsuccessful, failure information is output and the program is terminated. Otherwise, the next round of calculation is continued. And if all the rounds are calculated successfully, outputting the power limiting schemes of all the rounds.
According to the steps, calculation is performed in Matlab environment programming, and the electricity limiting schemes of all enterprises A-F can be obtained only in 19.76s, wherein the electricity limiting schemes corresponding to the enterprise users in the table 2 are shown in the table 3. Compared with the traditional manual programming mode which takes a few hours or even days, the automatic programming method provided by the invention greatly improves the efficiency.
TABLE 3 Enterprise Power limiting scheme
Analysis of tables 2 and 3 shows that enterprises 1 and 2 are 5-th-order daily peak-shifting avoidance users, the power limiting ratios of the A round are 565.5158/(5592.53-1250) = 13.0227%, 18.06382/(338.71-200) = 13.0227%, and the power limiting ratios of the B round are 29.4534% and 29.4534%, respectively. The power limiting ratio of enterprises 1 and 2 is the same (the power limiting ratio of C-F rounds of enterprises 1 and 2 is the same), so that the fair power limiting requirement is met. Second, the power limiting ratio of each round of enterprises 1 and 2 is in the range of the corresponding level and round of table 1, and the power limiting ratio of the next round is not lower than the power limiting ratio of the previous round, and the result shows that the formulaThis is true.
Enterprise 3 is a level 3 user who should not participate in the electricity limits for two rounds at A, B according to table 1, and the results in table 3 verify the conclusion; peak Zhou Cuobi, 5, users 4 and 5, require continuous stops compared to enterprise 3. Taking enterprise 4 as an example, it limits electricity only on Saturday on round A, on round B, on Saturday and Sunday, on round C, on Friday-Sunday, on round D, on Wednesday-Sunday, on round E and on round F, on Saturday-Sunday, the above results illustrate that the continuous stop constraint condition proposed by the invention is satisfied. In addition, the power limiting ratio of enterprises 4 and 5 in the round A (1 day stop in the round A) is 1/7= 14.2857%, and the power limiting ratio of the enterprises 4 and 5 in the round A is only 1.2630% different from that of the users 1 and 2 in the same class of daily peak avoidance, so that the fairness of the compiling method provided by the invention is further verified.
As shown in FIG. 3, FIG. 3 is a bar graph of the A-F wheel limit indicators and the actual limit loads of each wheel provided by the embodiment of the invention. In fig. 3, six horizontal dashed lines respectively correspond to the electricity limiting indexes of the wheels a to F from bottom to top, six column diagrams respectively correspond to the actual electricity limiting loads of the wheels a to F, wherein each column comprises 7 small columns, and each column corresponds to the actual electricity limiting loads of the wheels from one week to one week. The result shows that the automatic programming method of the ordered electricity limiting scheme provided by the invention can realize fair electricity limiting and simultaneously reduce the loss of enterprises caused by electricity limiting.
According to the obtained user information, the users are divided into a first class of users and a second class of users, an objective function is built by taking the sum of the electricity limiting load values of the users to be minimum and the difference of the electricity limiting proportion of the first class of users and the electricity limiting proportion of the second class of users to be minimum as a target, complete constraint conditions are built by combining the electricity limiting indexes of each round and the upper limit of the electricity limiting proportion, and a multi-round electricity limiting scheme is output through multi-round solving, so that the fairness of orderly electricity using scheme programming is improved, the loss brought by electricity limiting to the users is reduced, and the programming efficiency is improved.
Embodiment two:
corresponding to the embodiment of the orderly power consumption automatic programming method facing the multi-round power limiting, the embodiment of the invention also provides a computer storage medium, wherein a computer program is stored on the computer storage medium, and the program realizes any orderly power consumption automatic programming method facing the multi-round power limiting when being executed by a processor.
Embodiment III:
corresponding to the embodiment of the orderly power consumption automatic programming method facing the multi-round power limiting, the embodiment of the invention also provides a terminal device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes any orderly power consumption automatic programming method facing the multi-round power limiting when executing the computer program.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Claims (6)
1. An automatic programming method for orderly power utilization facing multi-round power limiting is characterized by comprising the following steps:
acquiring user information of a plurality of users, wherein the user information is used for representing the electricity utilization characteristics of the users, the users are classified into a first type user and a second type user according to whether the users are continuous production type, if yes, the users are the first type user, and if not, the users are the second type user;
constructing an objective function by taking the minimum sum of the electricity limiting load values of the plurality of users and the minimum difference of the electricity limiting proportion of the first type of users and the second type of users as targets;
determining constraint conditions matched with the objective function according to the user information, the limiting targets of all rounds and the upper limit value of the limiting proportion of all rounds, wherein the limiting targets of all rounds and the upper limit value of the limiting proportion of all rounds are preset values;
according to constraint conditions matched with the objective function and the user information, carrying out multi-round solving on the objective function to respectively obtain the electricity limiting load values of the users in each round of electricity limiting;
the user information includes:
user number, user type, maximum allowable electricity limiting load value, electricity utilization level, ordering weight and industry category;
the objective function is:
，/>，/>；
wherein ,、/>respectively-> and />Weights of (2); />An actual daily electricity limiting load value for a first class of users m of the kth electricity utilization level of the s-th round; />The actual electricity limiting load value of the second class user n of the kth electricity utilization level of the s-th round in the t-th day in one period; />、/>The electricity limiting proportion of the first class of users and the second class of users of the current power utilization level of the kth round is respectively; />Is the sum of the limit load values of the several users, < >>A difference between the electricity limiting ratios for the first type of users and the second type of users; t is the number of days of a cycle; k is the number of electricity utilization levels; />The number of first class users for the kth power usage level; />The number of the second class of users for the kth power utilization level; s is the electricity limiting round;
the constraint condition matched with the objective function is determined according to the user information, the limit electric targets and the limit electric proportion upper limit value of each round, and the constraint condition comprises the following steps:
distributing corresponding electricity limiting priority according to the sorting weight of the user, and determining an electricity limiting sequence constraint condition; wherein, the larger the sorting weight is, the higher the electricity limiting priority is;
determining a cross-wheel association constraint condition according to the limiting proportion of the user in the previous-wheel limiting and the upper limit value of the limiting proportion of each wheel; wherein, the limiting proportion of the user on the current wheel is larger than or equal to the limiting proportion of the previous wheel and smaller than or equal to the upper limit value of the limiting proportion of the current wheel;
determining a limit electric level constraint condition according to the electric level of the user; wherein, the electricity limiting proportion of the users with low electricity consumption level is smaller than or equal to the electricity limiting proportion of the users with high electricity consumption level;
determining a first-class user electricity limiting constraint condition according to the maximum allowable electricity limiting load value of the first-class user;
determining a second class user electricity limiting constraint condition according to the maximum allowable electricity limiting load value of the second class user;
determining a limiting index constraint condition according to the lowest limiting load value; wherein the lowest daily electrical load value is a preset value;
determining industry insurance constraint conditions according to the total number of users in the same industry in the second class of users; wherein the number of users in the second class of users in the same industry with a limit electric power ratio greater than 0 is smaller than the total number of users in the industry;
determining continuous stop constraint conditions according to the current wheel limiting proportion of the second class user;
and determining fairness constraint conditions according to the electricity utilization level of the user and the electricity limiting targets of each round.
2. A method for automatically programming orderly power consumption for limiting electricity in multiple rounds according to claim 1, wherein the number of power consumption levels is 5, and the power consumption levels are sequentially increased from 1 st level to 5 th level.
3. A method for automatic programming of orderly power consumption for multiple rounds of power limiting according to claim 1, wherein said power limiting turns s are greater than 1.
4. A multi-round electricity limiting oriented orderly electricity utilization automatic programming method according to claim 1, wherein the multi-round solving algorithm is a branch-and-bound algorithm, and the output of the previous round is taken as the input of the next round.
5. A computer storage medium having stored thereon a computer program which, when executed by a processor, implements a method as claimed in any one of claims 1 to 4.
6. A terminal device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any one of claims 1 to 4 when executing the computer program.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310671259.8A CN116402319B (en) | 2023-06-08 | 2023-06-08 | Multi-round electricity limiting oriented ordered electricity utilization automatic programming method, medium and equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310671259.8A CN116402319B (en) | 2023-06-08 | 2023-06-08 | Multi-round electricity limiting oriented ordered electricity utilization automatic programming method, medium and equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116402319A CN116402319A (en) | 2023-07-07 |
| CN116402319B true CN116402319B (en) | 2023-09-05 |
Family
ID=87014584
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310671259.8A Active CN116402319B (en) | 2023-06-08 | 2023-06-08 | Multi-round electricity limiting oriented ordered electricity utilization automatic programming method, medium and equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116402319B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117291401B (en) * | 2023-11-24 | 2024-02-02 | 成都汉度科技有限公司 | Ordered power utilization control method and system for power utilization peak period |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103235980A (en) * | 2013-04-08 | 2013-08-07 | 广东电网公司信息中心 | Power consumption management off-peak strategy optimization method based on multi-objective programming |
| CN110738428A (en) * | 2019-10-23 | 2020-01-31 | 四川万益能源科技有限公司 | Ordered power utilization load reduction demand decomposition method based on rotation decomposition |
| CN114707817A (en) * | 2022-03-16 | 2022-07-05 | 国网湖南省电力有限公司 | Adjustable load prediction method and system participating in ordered power utilization users |
| CN114757539A (en) * | 2022-04-19 | 2022-07-15 | 国网浙江省电力有限公司经济技术研究院 | Method, device, equipment and medium for compiling orderly power utilization scheme |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150294245A1 (en) * | 2014-04-14 | 2015-10-15 | Ajay R Nagar | Method and system for handling program, project and asset scheduling management with reserves management and application integration |
-
2023
- 2023-06-08 CN CN202310671259.8A patent/CN116402319B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103235980A (en) * | 2013-04-08 | 2013-08-07 | 广东电网公司信息中心 | Power consumption management off-peak strategy optimization method based on multi-objective programming |
| CN110738428A (en) * | 2019-10-23 | 2020-01-31 | 四川万益能源科技有限公司 | Ordered power utilization load reduction demand decomposition method based on rotation decomposition |
| CN114707817A (en) * | 2022-03-16 | 2022-07-05 | 国网湖南省电力有限公司 | Adjustable load prediction method and system participating in ordered power utilization users |
| CN114757539A (en) * | 2022-04-19 | 2022-07-15 | 国网浙江省电力有限公司经济技术研究院 | Method, device, equipment and medium for compiling orderly power utilization scheme |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116402319A (en) | 2023-07-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Ren | New energy vehicle in China for sustainable development: Analysis of success factors and strategic implications | |
| Hoekstra et al. | Creating agent‐based energy transition management models that can uncover profitable pathways to climate change mitigation | |
| Li et al. | A multi-criterion decision making for sustainability assessment of hydrogen production technologies based on objective grey relational analysis | |
| CN116402319B (en) | Multi-round electricity limiting oriented ordered electricity utilization automatic programming method, medium and equipment | |
| Yang et al. | A self-learning TLBO based dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads | |
| Zhou | China's development of low-carbon eco-cities and associated indicator systems | |
| Saqib et al. | Are technological innovations and green energy prosperity swiftly reduce environmental deficit in China and United States? Learning from two sides of environmental sustainability | |
| Andrews-Speed et al. | China as a global clean energy champion: lifting the veil | |
| CN103745291B (en) | Based on the multiple target ordered electric sort method of electrical characteristics | |
| Du et al. | Multi-renewable management: Interactions between wind and solar within uncertain technology ecological system | |
| CN109272205B (en) | Generalized load characteristic analysis method and device | |
| CN113822547A (en) | Refined demand side management comprehensive information platform system and management method | |
| Bosselman et al. | Energy, economics and the Environment: cases and Materials | |
| Schmidt et al. | 100 Pioneers in Efficient Resource Management: Best practice cases from producing companies | |
| CN106469420A (en) | Electric energy consumption evaluation methodology and evaluation system | |
| Chen et al. | Energy-efficient hybrid flow-shop scheduling under time-of-use and ladder electricity tariffs | |
| Wang et al. | Can the target responsibility system of air pollution control achieve a win-win situation of pollution reduction and efficiency enhancement? | |
| Henríquez | Energy sources for sustainable transportation and urban development | |
| CN106991580A (en) | Pricing method of the asymmetric manufacturer with combined recovery business under monopolization take-back model | |
| Wietschel et al. | Economic impacts of hydrogen as an energy carrier in European countries | |
| Taylor et al. | The role of technological innovation in meeting California’s greenhouse gas emission targets | |
| CN111008723A (en) | Optimization method for design of distributed energy PEV charging station | |
| CN114692396A (en) | Supply and demand optimal configuration system suitable for urban energy system | |
| Xu et al. | A Study on Electric Vehicles Participating in the Load Regulation of Urban Complexes | |
| Ma et al. | Comprehensive evaluation of renewable energy for power projects based on CA-DEA model |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |