CN111668851A - Electric heating load adjustment optimization method and device - Google Patents

Electric heating load adjustment optimization method and device Download PDF

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Publication number
CN111668851A
CN111668851A CN202010406056.2A CN202010406056A CN111668851A CN 111668851 A CN111668851 A CN 111668851A CN 202010406056 A CN202010406056 A CN 202010406056A CN 111668851 A CN111668851 A CN 111668851A
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load
electric heating
iteration
heating load
regulation efficiency
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Inventor
宫飞翔
周颖
李德智
田世明
霍现旭
李树鹏
韩凝晖
董明宇
陈宋宋
石坤
龚桃荣
潘明明
谢尊辰
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State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd CEPRI
State Grid Tianjin Electric Power Co Ltd
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State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd CEPRI
State Grid Tianjin Electric Power Co Ltd
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    • 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
    • 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]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/222—Demand response systems, e.g. load shedding, peak shaving

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Abstract

The invention relates to an electric heating load regulation optimization method and a device, comprising the following steps: substituting the obtained load distribution amount of the electric heating loads into a load regulation efficiency optimization model to obtain the initial value of the load regulation efficiency of each electric heating load; based on the initial value of the load adjustment efficiency of each electric heating load, the load distribution quantity of the electric heating load input into the load adjustment efficiency optimization model in the iterative solution process is corrected by using a dual model of the load adjustment efficiency optimization model, and an optimal load adjustment scheme is determined according to the load adjustment quantity of each electric heating load obtained in the iterative solution process; according to the invention, the optimal load regulation and control scheme is obtained by optimizing the load regulation efficiency of the electric heating load, and the problems of low terminal voltage and low load utilization rate of the power distribution network caused by the increase of the electric heating load are solved.

Description

Electric heating load adjustment optimization method and device
Technical Field
The invention relates to the technical field of power planning and scheduling, in particular to an electric heating load regulation optimization method and device.
Background
Compared with the conventional power load, the energy consumption behavior of the electric heating load often has obvious characteristics of climate and behavior drivability, and can bring important influence on the safe operation of the power distribution network. When a new load peak appears, the load rate of the multi-ground power grid touches or exceeds a warning line, and new difficulty is brought to the construction and reconstruction work of the power distribution network; meanwhile, the instantaneous starting current surge of large-scale electric heating load can bring frequent low-voltage phenomenon to a power distribution network, and even bring trouble to enterprise production and normal electricity utilization of residents in severe cases.
The application of various electric heating load devices exposes a plurality of problems, the electric heating load investment is increased, the peak-valley difference of a power grid is increased, the terminal voltage of the power distribution network is too low in the peak period of power utilization, the utilization rate of the electric heating load devices is low, the effect of the electric heating load on the aspects of exerting clean energy consumption and the like is not obvious, and the operation cost is generally high. And the types of the electric heating loads are various, the rated parameters and the heating requirements are different, and when the electric heating users participate in the demand response, the task difference accurate quantification capability of the electric heating load regulation is insufficient.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide an electric heating load regulation and optimization method and device, which solve the problems of low terminal voltage of a power distribution network, low utilization rate of electric heating loads and poor new energy consumption caused by the large-scale electric heating load application.
The invention provides an electric heating load adjustment and optimization method, which is improved in that the method comprises the following steps:
substituting the obtained load distribution amount of the electric heating loads into a load regulation efficiency optimization model to obtain the initial value of the load regulation efficiency of each electric heating load;
and based on the initial value of the load adjustment efficiency of each electric heating load, correcting the load distribution quantity of the electric heating load input into the load adjustment efficiency optimization model in the iterative solution process by using a dual model of the load adjustment efficiency optimization model, and determining an optimal load adjustment scheme according to the load adjustment quantity of each electric heating load obtained in the iterative solution process.
Preferably, the obtaining an initial value of load adjustment efficiency of each electric heating load by substituting the obtained load distribution amount of the electric heating load into the load adjustment efficiency optimization model includes:
substituting the obtained load distribution amount of each electric heating load into a load regulation efficiency optimization model, and solving the load regulation efficiency optimization model to obtain a total load regulation efficiency value;
and determining the initial value of the load regulation efficiency of each electric heating load based on the total load regulation efficiency value and the proportion of the load regulation efficiency value of each electric heating load to the total load regulation efficiency value.
Preferably, the load regulation efficiency optimization model of the electric heating load is constructed based on a goal of maximizing the load regulation efficiency of the electric heating load, and the specific construction process includes:
determining a load regulation efficiency optimization model of the electric heating load according to the following formula:
Figure BDA0002491314540000021
in the formula, βoAdjusting the efficiency value, lambda, for the total load of the electric heating loadjThe ratio of the load regulation efficiency value of the jth electric heating load to the total load regulation efficiency value of the electric heating loads, j ∈ [1, N]N is the total electric heating load, xijResource input of ith for jth electric heating load, xioFor the ith total resource input, i ∈ [1, M]M is the total number of resource input types, yrjR desired output, y for j electric heating loadroR ∈ [1, S ] for the r-th desired throughput]S is the total number of expected output types, bjLoad distribution of jth electric heating load, boThe total load distribution amount of the electric heating load is distributed.
Preferably, the determining an optimal load adjustment scheme based on the initial value of the load adjustment efficiency of each electric heating load by correcting the load distribution amount of the electric heating load input to the load adjustment efficiency optimization model in the iterative solution process using the dual model of the load adjustment efficiency optimization model and according to the load adjustment amount of each electric heating load obtained in the iterative solution process includes:
s1, initializing iteration times t, and taking the initial load adjustment efficiency value of each electric heating load as the load adjustment efficiency value of each electric heating load in the t iteration;
s2, substituting the load regulation efficiency values of the electric heating loads of the t iteration into a dual model of the load regulation efficiency optimization model, and solving the dual model to obtain load regulation quantity of the electric heating loads of the t iteration;
s3, correcting the load distribution quantity of each electric heating load of the t iteration according to the load adjustment quantity of each electric heating load of the t iteration;
s4, substituting the corrected load distribution amount of each electric heating load of the t iteration into a load regulation efficiency optimization model to obtain load regulation efficiency values of each electric heating load of the t +1 iteration;
s5. if βj,t+1-βj,tIf | ≧ βj,t＝βj,t+1And S2 is executed, otherwise, the load adjustment quantity of each electric heating load of the t iteration obtained by solving the dual model is used as the optimal load adjustment scheme, wherein βj,tAdjusting the efficiency rate for the load of the jth electric heating load for the tth iteration, βj,t+1The efficiency value is adjusted for the load of the jth electric heating load for the t +1 th iteration to be constant.
Preferably, the dual model of the load regulation efficiency optimization model is determined as follows:
Figure BDA0002491314540000031
in the formula urWeight coefficient for the r-th expected yield, viThe weight factor invested for the ith resource,
Figure BDA0002491314540000032
Figure BDA0002491314540000033
w is an unconstrained variable which is a variable,
Figure BDA0002491314540000034
Δ B is the load regulation target amount, Δ BjLoad regulation for jth electric heating load, a1Is a first decision parameter, a2Is the second decision parameter.
Further, the correcting the load distribution amount of each electric heating load in the t iteration according to the load adjustment amount of each electric heating load in the t iteration includes:
determining the t-th iteration station according to the load adjustment quantity of each electric heating load of the t-th iterationAverage value of load regulation quantity of electric heating load
Figure BDA0002491314540000036
；
Based on
Figure BDA0002491314540000037
And correcting the load distribution quantity of each electric heating load of the t iteration according to the following formula:
Figure BDA0002491314540000035
in the formula, bj,tLoad distribution amount, b 'for jth electric heating load at tth iteration'j,tAnd the load distribution quantity of the jth electric heating load is iterated for the corrected tth time.
Based on the same inventive concept, the invention also provides an electric heating load adjustment optimizing device, and the improvement is that the device comprises:
the first optimization module is used for substituting the acquired load distribution amount of the electric heating loads into the load regulation efficiency optimization model to obtain the initial value of the load regulation efficiency of each electric heating load;
and the second optimization module is used for correcting the load distribution quantity of the electric heating loads input into the load regulation efficiency optimization model in the iterative solution process by using the dual model of the load regulation efficiency optimization model based on the initial value of the load regulation efficiency of each electric heating load, and determining an optimal load regulation scheme according to the load regulation quantity of each electric heating load obtained in the iterative solution process.
Preferably, the first optimization module is specifically configured to:
substituting the obtained load distribution amount of each electric heating load into a load regulation efficiency optimization model, and solving the load regulation efficiency optimization model to obtain a total load regulation efficiency value;
and determining the initial value of the load regulation efficiency of each electric heating load based on the total load regulation efficiency value and the proportion of the load regulation efficiency value of each electric heating load to the total load regulation efficiency value.
Preferably, the load regulation efficiency optimization model of the electric heating load is constructed based on a goal of maximizing the load regulation efficiency of the electric heating load, and the specific construction process includes:
determining a load regulation efficiency optimization model of the electric heating load according to the following formula:
Figure BDA0002491314540000041
in the formula, βoAdjusting the efficiency value, lambda, for the total load of the electric heating loadjThe ratio of the load regulation efficiency value of the jth electric heating load to the total load regulation efficiency value of the electric heating loads, j ∈ [1, N]N is the total electric heating load, xijResource input of ith for jth electric heating load, xioFor the ith total resource input, i ∈ [1, M]M is the total number of resource input types, yrjR desired output, y for j electric heating loadroR ∈ [1, S ] for the r-th desired throughput]S is the total number of expected output types, bjLoad distribution of jth electric heating load, boThe total load distribution amount of the electric heating load is distributed.
Preferably, the second optimization module is specifically configured to:
s1, initializing iteration times t, and taking the initial load adjustment efficiency value of each electric heating load as the load adjustment efficiency value of each electric heating load in the t iteration;
s2, substituting the load regulation efficiency values of the electric heating loads of the t iteration into a dual model of the load regulation efficiency optimization model, and solving the dual model to obtain load regulation quantity of the electric heating loads of the t iteration;
s3, correcting the load distribution quantity of each electric heating load of the t iteration according to the load adjustment quantity of each electric heating load of the t iteration;
s4, substituting the corrected load distribution amount of each electric heating load of the t iteration into a load regulation efficiency optimization model to obtain load regulation efficiency values of each electric heating load of the t +1 iteration;
s5. if βj,t+1-βj,tIf | ≧ βj,t＝βj,t+1And S2 is executed, otherwise, the load adjustment quantity of each electric heating load of the t iteration obtained by solving the dual model is used as the optimal load adjustment scheme, wherein βj,tAdjusting the efficiency rate for the load of the jth electric heating load for the tth iteration, βj,t+1The efficiency value is adjusted for the load of the jth electric heating load for the t +1 th iteration to be constant.
Preferably, the dual model of the load regulation efficiency optimization model is determined as follows:
Figure BDA0002491314540000051
in the formula urWeight coefficient for the r-th expected yield, viThe weight factor invested for the ith resource,
Figure BDA0002491314540000061
Figure BDA0002491314540000062
w is an unconstrained variable which is a variable,
Figure BDA0002491314540000063
Δ B is the load regulation target amount, Δ BjLoad regulation for jth electric heating load, a1Is a first decision parameter, a2Is the second decision parameter.
Further, the correcting the load distribution amount of each electric heating load in the t iteration according to the load adjustment amount of each electric heating load in the t iteration includes:
determining the average value of the load adjustment quantity of all the electric heating loads in the t iteration according to the load adjustment quantity of each electric heating load in the t iteration
Figure BDA0002491314540000065
；
Based on
Figure BDA0002491314540000066
And correcting the load distribution quantity of each electric heating load of the t iteration according to the following formula:
Figure BDA0002491314540000064
in the formula, bj,tLoad distribution amount, b 'for jth electric heating load at tth iteration'j,tAnd the load distribution quantity of the jth electric heating load is iterated for the corrected tth time.
Compared with the closest prior art, the invention has the following beneficial effects:
in the technical scheme of the invention, the load distribution quantity of the obtained electric heating loads is substituted into a load regulation efficiency optimization model to obtain the initial value of the load regulation efficiency of each electric heating load; and based on the initial value of the load adjustment efficiency of each electric heating load, correcting the load distribution quantity of the electric heating load input into the load adjustment efficiency optimization model in the iterative solution process by using a dual model of the load adjustment efficiency optimization model, and determining an optimal load adjustment scheme according to the load adjustment quantity of each electric heating load obtained in the iterative solution process. According to the method, the load distribution quantity of the electric heating loads input into the load regulation efficiency optimization model is continuously corrected by using the load regulation efficiency optimization model and the dual model thereof in the interactive iterative solving process, so that an optimal load regulation scheme is determined according to the load regulation quantity of each electric heating load obtained in the iterative solving process, the problems of low terminal voltage and low load utilization rate of a power distribution network are solved, and the consumption of new energy is improved to a certain extent;
according to the technical scheme, the load regulation efficiency model is established by taking the load regulation efficiency maximization as a target, so that the solved result is closer to the actual condition and the requirements of electric heating users are met.
Drawings
FIG. 1 is a flow chart of an electrical heating load regulation optimization method of the present invention;
fig. 2 is a schematic diagram of the electric heating load regulation optimizing device.
Detailed Description
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides an electric heating load adjustment and optimization method, as shown in fig. 1, the method comprises the following steps:
step 1, substituting the obtained load distribution amount of the electric heating loads into a load regulation efficiency optimization model to obtain the initial value of the load regulation efficiency of each electric heating load;
and 2, based on the initial value of the load adjustment efficiency of each electric heating load, correcting the load distribution quantity of the electric heating load input into the load adjustment efficiency optimization model in the iterative solution process by using a dual model of the load adjustment efficiency optimization model, and determining an optimal load adjustment scheme according to the load adjustment quantity of each electric heating load obtained in the iterative solution process.
In order to more clearly illustrate the objects of the present invention, the following examples are given to further illustrate the present invention.
In an embodiment of the present invention, in step 1, the load distribution amount of the obtained electric heating loads is substituted into the load regulation efficiency optimization model to obtain an initial value of load regulation efficiency of each electric heating load, including:
substituting the obtained load distribution amount of each electric heating load into a load regulation efficiency optimization model, and solving the load regulation efficiency optimization model to obtain a total load regulation efficiency value;
and determining the initial value of the load regulation efficiency of each electric heating load based on the total load regulation efficiency value and the proportion of the load regulation efficiency value of each electric heating load to the total load regulation efficiency value.
Specifically, the efficiency rate β is adjusted based on the total loadoDetermining the initial value of the load regulation efficiency of each electric heating load according to the following formula:
βj＝λjβo
in the formula, βjAdjusting the initial value of the efficiency, lambda, for the j-th electric heating loadjThe load regulation efficiency value of the jth electric heating load accounts for the proportion of the total load regulation efficiency value of the electric heating loads.
In an embodiment of the present invention, the load regulation efficiency optimization model of the electric heating load is constructed based on a goal of maximizing the load regulation efficiency of the electric heating load, and the specific construction process includes:
determining a load regulation efficiency optimization model of the electric heating load according to the following formula:
Figure BDA0002491314540000081
in the formula, βoAdjusting the efficiency value, lambda, for the total load of the electric heating loadjThe ratio of the load regulation efficiency value of the jth electric heating load to the total load regulation efficiency value of the electric heating loads, j ∈ [1, N]N is the total electric heating load, xijResource input of ith for jth electric heating load, xioFor the ith total resource input, i ∈ [1, M]M is the total number of resource input types, yrjR desired output, y for j electric heating loadroR ∈ [1, S ] for the r-th desired throughput]S is the total number of expected output types, bjLoad distribution of jth electric heating load, boThe total load distribution amount of the electric heating load is distributed.
The optimization direction of the load regulation efficiency optimization model is to seek the maximum increment of the expected output and the maximum regulation amount of the unexpected output which are matched with each other, and the optimal objective function value is the total load regulation efficiency βoThe larger the load cell is, the better the performance of the load cell under evaluation is.
The resource investment is the resource which needs to be consumed for heating load adjustment, and comprises the influences of manpower, a regulation module and user comfort;
the expected output is the regulation and control benefits brought to the user and the power grid by regulating the load, including benefits brought by user subsidies, value-added services and power grid peak shaving.
In the embodiment of the invention, the optimal load regulation scheme is solved by iteration through the dual model of the load regulation efficiency optimization model.
Specifically, the step 2, based on the initial value of the load adjustment efficiency of each electric heating load, determining the load distribution amount of the electric heating load input to the load adjustment efficiency optimization model in the iterative solution process by using the dual model of the load adjustment efficiency optimization model, and determining the optimal load adjustment scheme according to the load adjustment amount of each electric heating load obtained in the iterative solution process, includes:
s1, initializing iteration times t, and taking the initial load adjustment efficiency value of each electric heating load as the load adjustment efficiency value of each electric heating load in the t iteration;
s2, substituting the load regulation efficiency values of the electric heating loads of the t iteration into a dual model of the load regulation efficiency optimization model, and solving the dual model to obtain load regulation quantity of the electric heating loads of the t iteration;
s3, correcting the load distribution quantity of each electric heating load of the t iteration according to the load adjustment quantity of each electric heating load of the t iteration;
s4, substituting the corrected load distribution amount of each electric heating load of the t iteration into a load regulation efficiency optimization model to obtain load regulation efficiency values of each electric heating load of the t +1 iteration;
s5. if βj,t+1-βj,tIf | ≧ βj,t＝βj,t+1And S2 is executed, otherwise, the load adjustment quantity of each electric heating load of the t iteration obtained by solving the dual model is used as the optimal load adjustment scheme, wherein βj,tAdjusting the efficiency rate for the load of the jth electric heating load for the tth iteration, βj,t+1For the jth electric heating load of the t +1 th iterationThe load adjustment efficiency value of (1) is constant.
Specifically, the modifying the load distribution amount of each electric heating load in the t iteration according to the load adjustment amount of each electric heating load in the t iteration includes:
determining the average value of the load adjustment quantity of all the electric heating loads in the t iteration according to the load adjustment quantity of each electric heating load in the t iteration
Figure BDA0002491314540000091
Based on
Figure BDA0002491314540000092
And correcting the load distribution quantity of each electric heating load of the t iteration according to the following formula:
Figure BDA0002491314540000093
in the formula, bj,tLoad distribution amount, b 'for jth electric heating load at tth iteration'j,tAnd the load distribution quantity of the jth electric heating load is iterated for the corrected tth time.
In an embodiment of the invention, the initial dual model (1) of the load regulation efficiency optimization model is:
Figure BDA0002491314540000094
when the total target of load regulation is Δ B, to accomplish this, each load unit needs to contribute Δ BjI.e. by
Figure BDA0002491314540000095
Wherein Δ bjAnd the value of more than or equal to 0 is an unknown variable which needs to be obtained by solving the dual model.
Based on the actual situation, the regulation planning of the load needs to satisfy two basic and reasonable criteria: firstly, the load regulation proportion of each load unit needs to be controlled within a certain range; and secondly, the load regulation efficiency value of any load unit cannot be reduced after load regulation.
The planning idea is substituted into the initial dual model (1) to obtain an initial dual model (2) which determines the load regulation scheme from the load unit perspective as follows.
Figure BDA0002491314540000101
In the initial dual model (2), a1And a2Non-negative parameters predetermined by the decision maker of the load cell, representing the allowable deviation of the load cell from the upper and lower limits of the total load regulation ratio, 0 ≦ βj≤1；
Wherein the content of the first and second substances,
Figure BDA0002491314540000102
and
Figure BDA0002491314540000103
the two basic planning criteria are respectively guaranteed.
Due to the quadratic term w Δ bjThe objective function and the constraint condition exist in the initial dual model (2) at the same time, so the initial dual model (2) is a nonlinear programming problem, and w delta b is set for linearizing the initial dual modeljIs a new variable rjSince w is an unconstrained variable, r is used in the model (2)jSubstitution of Δ bjAnd guarantee the constraint condition
Figure BDA0002491314540000104
Is not influenced in the unequal number directions, under the constraint condition
Figure BDA0002491314540000111
Multiplying both sides of the equal sign and the unequal sign by the absolute value | w | of w simultaneously to obtain the following initial dual model (3):
Figure BDA0002491314540000112
order to
Figure BDA0002491314540000113
Then
Figure BDA0002491314540000114
Can thus be used in the model (3)
Figure BDA0002491314540000115
And
Figure BDA0002491314540000116
replace | w | and w and get the following model (4):
Figure BDA0002491314540000121
due to the fact that
Figure BDA0002491314540000122
If there is, the model (4) is still non-linear programming, so further order
Figure BDA0002491314540000123
To obtain
Figure BDA0002491314540000124
In the introduction of new variables
Figure BDA0002491314540000125
And
Figure BDA0002491314540000126
and then, equivalently obtaining a dual model corresponding to the load regulation efficiency optimization model of the electric heating load by the model (4), and determining the dual model corresponding to the load regulation efficiency optimization model of the electric heating load according to the following formula:
Figure BDA0002491314540000127
in the above process, ω is the objective function of the dual model, urWeight coefficient for the r-th expected yield, viRight to invest for ith resourceThe weight coefficient of the light beam is calculated,
Figure BDA0002491314540000131
w is an unconstrained variable which is a variable,
Figure BDA0002491314540000132
is the first over-measure of the unconstrained variable,
Figure BDA0002491314540000133
is a second over-measure of the unconstrained variable,
Figure BDA0002491314540000134
Figure BDA0002491314540000135
is a first variable of the jth electric heating load,
Figure BDA0002491314540000136
Figure BDA0002491314540000137
is a second variable of the jth electric heating load,
Figure BDA0002491314540000138
Δ B is the load regulation target amount, Δ BjLoad regulation for jth electric heating load, a1Is a first decision parameter, a2Is the second decision parameter.
Specifically, the average value of the load adjustment amounts of all the electric heating loads in the t iteration is determined according to the load adjustment amounts of all the electric heating loads in the t iteration
Figure BDA0002491314540000139
The method comprises the following steps:
Figure BDA00024913145400001310
in the formula,. DELTA.bj,tAnd (4) adjusting the load for the t-1 th iteration of the jth electric heating load.
Based on the same inventive concept, the invention also provides an electric heating load adjustment optimizing device, as shown in fig. 2, the device comprises:
the first optimization module is used for substituting the acquired load distribution amount of the electric heating loads into the load regulation efficiency optimization model to obtain the initial value of the load regulation efficiency of each electric heating load;
and the second optimization module is used for correcting the load distribution quantity of the electric heating loads input into the load regulation efficiency optimization model in the iterative solution process by using the dual model of the load regulation efficiency optimization model based on the initial value of the load regulation efficiency of each electric heating load, and determining an optimal load regulation scheme according to the load regulation quantity of each electric heating load obtained in the iterative solution process.
Preferably, the first optimization module is specifically configured to:
substituting the obtained load distribution amount of each electric heating load into a load regulation efficiency optimization model, and solving the load regulation efficiency optimization model to obtain a total load regulation efficiency value;
and determining the initial value of the load regulation efficiency of each electric heating load based on the total load regulation efficiency value and the proportion of the load regulation efficiency value of each electric heating load to the total load regulation efficiency value.
Preferably, the load regulation efficiency optimization model of the electric heating load is constructed based on a goal of maximizing the load regulation efficiency of the electric heating load, and the specific construction process includes:
determining a load regulation efficiency optimization model of the electric heating load according to the following formula:
Figure BDA0002491314540000141
in the formula, βoAdjusting the efficiency value, lambda, for the total load of the electric heating loadjThe ratio of the load regulation efficiency value of the jth electric heating load to the total load regulation efficiency value of the electric heating loads, j ∈ [1, N]N is the total electric heating load, xijResource input of ith for jth electric heating load, xioFor the ith total resource input, i ∈ [1, M]M is the total number of resource input types, yrjR desired output, y for j electric heating loadroR ∈ [1, S ] for the r-th desired throughput]S is the total number of expected output types, bjLoad distribution of jth electric heating load, boThe total load distribution amount of the electric heating load is distributed.
Preferably, the second optimization module is specifically configured to:
s1, initializing iteration times t, and taking the initial load adjustment efficiency value of each electric heating load as the load adjustment efficiency value of each electric heating load in the t iteration;
s2, substituting the load regulation efficiency values of the electric heating loads of the t iteration into a dual model of the load regulation efficiency optimization model, and solving the dual model to obtain load regulation quantity of the electric heating loads of the t iteration;
s3, correcting the load distribution quantity of each electric heating load of the t iteration according to the load adjustment quantity of each electric heating load of the t iteration;
s4, substituting the corrected load distribution amount of each electric heating load of the t iteration into a load regulation efficiency optimization model to obtain load regulation efficiency values of each electric heating load of the t +1 iteration;
s5. if βj,t+1-βj,tIf | ≧ βj,t＝βj,t+1And S2 is executed, otherwise, the load adjustment quantity of each electric heating load of the t iteration obtained by solving the dual model is used as the optimal load adjustment scheme, wherein βj,tAdjusting the efficiency rate for the load of the jth electric heating load for the tth iteration, βj,t+1The efficiency value is adjusted for the load of the jth electric heating load for the t +1 th iteration to be constant.
Preferably, the dual model of the load regulation efficiency optimization model is determined as follows:
Figure BDA0002491314540000151
in the formula urWeight coefficient for the r-th expected yield, viFor the ith assetThe weight factor of the source investment is,
Figure BDA0002491314540000152
Figure BDA0002491314540000153
w is an unconstrained variable which is a variable,
Figure BDA0002491314540000154
Δ B is the load regulation target amount, Δ BjLoad regulation for jth electric heating load, a1Is a first decision parameter, a2Is the second decision parameter.
Further, the correcting the load distribution amount of each electric heating load in the t iteration according to the load adjustment amount of each electric heating load in the t iteration includes:
determining the average value of the load adjustment quantity of all the electric heating loads in the t iteration according to the load adjustment quantity of each electric heating load in the t iteration
Figure BDA0002491314540000155
Based on
Figure BDA0002491314540000156
And correcting the load distribution quantity of each electric heating load of the t iteration according to the following formula:
Figure BDA0002491314540000157
in the formula, bj,tLoad distribution amount, b 'for jth electric heating load at tth iteration'j,tAnd the load distribution quantity of the jth electric heating load is iterated for the corrected tth time.
In summary, in the technical solution of the present invention, the load distribution amount of the obtained electric heating loads is substituted into the load regulation efficiency optimization model to obtain the initial value of the load regulation efficiency of each electric heating load; and based on the initial value of the load adjustment efficiency of each electric heating load, correcting the load distribution quantity of the electric heating load input into the load adjustment efficiency optimization model in the iterative solution process by using a dual model of the load adjustment efficiency optimization model, and determining an optimal load adjustment scheme according to the load adjustment quantity of each electric heating load obtained in the iterative solution process. According to the method, the load distribution quantity of the electric heating loads input into the load regulation efficiency optimization model is continuously corrected by using the load regulation efficiency optimization model and the dual model thereof in the interactive iterative solving process, so that an optimal load regulation scheme is determined according to the load regulation quantity of each electric heating load obtained in the iterative solving process, the problems of low terminal voltage and low load utilization rate of a power distribution network are solved, and the consumption of new energy is improved to a certain extent;
according to the technical scheme, the load regulation efficiency model is established by taking the load regulation efficiency maximization as a target, so that the solved result is closer to the actual condition and the requirements of electric heating users are met.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.

Claims (12)

1. An electric heating load regulation optimization method is characterized by comprising the following steps:
substituting the obtained load distribution amount of the electric heating loads into a load regulation efficiency optimization model to obtain the initial value of the load regulation efficiency of each electric heating load;
and based on the initial value of the load adjustment efficiency of each electric heating load, correcting the load distribution quantity of the electric heating load input into the load adjustment efficiency optimization model in the iterative solution process by using a dual model of the load adjustment efficiency optimization model, and determining an optimal load adjustment scheme according to the load adjustment quantity of each electric heating load obtained in the iterative solution process.
2. The method according to claim 1, wherein the step of substituting the obtained load distribution amount of the electric heating loads into the load regulation efficiency optimization model to obtain an initial value of the load regulation efficiency of each electric heating load comprises:
substituting the obtained load distribution amount of each electric heating load into a load regulation efficiency optimization model, and solving the load regulation efficiency optimization model to obtain a total load regulation efficiency value;
and determining the initial value of the load regulation efficiency of each electric heating load based on the total load regulation efficiency value and the proportion of the load regulation efficiency value of each electric heating load to the total load regulation efficiency value.
3. The method according to claim 1 or 2, wherein the load regulation efficiency optimization model of the electric heating load is constructed based on the goal of maximizing the load regulation efficiency of the electric heating load, and the specific construction process comprises the following steps:
determining a load regulation efficiency optimization model of the electric heating load according to the following formula:
Figure FDA0002491314530000011
in the formula, βoAdjusting the efficiency value, lambda, for the total load of the electric heating loadjThe ratio of the load regulation efficiency value of the jth electric heating load to the total load regulation efficiency value of the electric heating loads, j ∈ [1, N]N is the total electric heating load, xijResource input of ith for jth electric heating load, xioFor the ith total resource input, i ∈ [1, M]M is the total number of resource input types, yrjR desired output, y for j electric heating loadroR ∈ [1, S ] for the r-th desired throughput]S is the total number of expected output types, bjLoad distribution of jth electric heating load, boThe total load distribution amount of the electric heating load is distributed.
4. The method according to claim 1, wherein the modifying the load distribution amount of the electric heating load input to the load regulation efficiency optimization model in the iterative solution process by using the dual model of the load regulation efficiency optimization model based on the initial value of the load regulation efficiency of each electric heating load, and determining the optimal load regulation scheme according to the load regulation amount of each electric heating load obtained in the iterative solution process, comprises:
s1, initializing iteration times t, and taking the initial load adjustment efficiency value of each electric heating load as the load adjustment efficiency value of each electric heating load in the t iteration;
s2, substituting the load regulation efficiency values of the electric heating loads of the t iteration into a dual model of the load regulation efficiency optimization model, and solving the dual model to obtain load regulation quantity of the electric heating loads of the t iteration;
s3, correcting the load distribution quantity of each electric heating load of the t iteration according to the load adjustment quantity of each electric heating load of the t iteration;
s4, substituting the corrected load distribution amount of each electric heating load of the t iteration into a load regulation efficiency optimization model to obtain load regulation efficiency values of each electric heating load of the t +1 iteration;
s5. if βj,t+1-βj,tIf | ≧ βj,t＝βj,t+1And S2 is executed, otherwise, the load adjustment quantity of each electric heating load of the t iteration obtained by solving the dual model is used as the optimal load adjustment scheme, wherein βj,tAdjusting the efficiency rate for the load of the jth electric heating load for the tth iteration, βj,t+1The efficiency value is adjusted for the load of the jth electric heating load for the t +1 th iteration to be constant.
5. The method of claim 1 or 4, wherein the dual model of the load regulation efficiency optimization model is determined as follows:
Figure FDA0002491314530000021
in the formula urWeight coefficient for the r-th expected yield, viThe weight factor invested for the ith resource,
Figure FDA0002491314530000031
Figure FDA0002491314530000032
w is an unconstrained variable which is a variable,
Figure FDA0002491314530000033
Δ B is the load regulation target amount, Δ BjLoad regulation for jth electric heating load, a1Is a first decision parameter, a2Is the second decision parameter.
6. The method according to claim 4, wherein the correcting the load distribution amount of each electric heating load in the t iteration according to the load adjustment amount of each electric heating load in the t iteration comprises:
determining the average value of the load adjustment quantity of all the electric heating loads in the t iteration according to the load adjustment quantity of each electric heating load in the t iteration
Figure FDA0002491314530000034
Based on
Figure FDA0002491314530000035
And correcting the load distribution quantity of each electric heating load of the t iteration according to the following formula:
Figure FDA0002491314530000036
in the formula, bj,tLoad distribution amount, b 'for jth electric heating load at tth iteration'j,tAnd the load distribution quantity of the jth electric heating load is iterated for the corrected tth time.
7. An electric heating load adjustment optimizing device, characterized in that, the device includes:
the first optimization module is used for substituting the acquired load distribution amount of the electric heating loads into the load regulation efficiency optimization model to obtain the initial value of the load regulation efficiency of each electric heating load;
and the second optimization module is used for correcting the load distribution quantity of the electric heating loads input into the load regulation efficiency optimization model in the iterative solution process by using the dual model of the load regulation efficiency optimization model based on the initial value of the load regulation efficiency of each electric heating load, and determining an optimal load regulation scheme according to the load regulation quantity of each electric heating load obtained in the iterative solution process.
8. The apparatus of claim 7, wherein the first optimization module is specifically configured to:
substituting the obtained load distribution amount of each electric heating load into a load regulation efficiency optimization model, and solving the load regulation efficiency optimization model to obtain a total load regulation efficiency value;
and determining the initial value of the load regulation efficiency of each electric heating load based on the total load regulation efficiency value and the proportion of the load regulation efficiency value of each electric heating load to the total load regulation efficiency value.
9. The device according to claim 7 or 8, wherein the load regulation efficiency optimization model of the electric heating load is constructed based on the goal of maximizing the load regulation efficiency of the electric heating load, and the specific construction process comprises the following steps:
determining a load regulation efficiency optimization model of the electric heating load according to the following formula:
Figure FDA0002491314530000041
in the formula, βoAdjusting the efficiency value, lambda, for the total load of the electric heating loadjThe load regulation efficiency value of the jth electric heating load accounts for the proportion of the total load regulation efficiency value of the electric heating loads,j∈[1,N]n is the total electric heating load, xijResource input of ith for jth electric heating load, xioFor the ith total resource input, i ∈ [1, M]M is the total number of resource input types, yrjR desired output, y for j electric heating loadroR ∈ [1, S ] for the r-th desired throughput]S is the total number of expected output types, bjLoad distribution of jth electric heating load, boThe total load distribution amount of the electric heating load is distributed.
10. The apparatus of claim 7, wherein the second optimization module is specifically configured to:
s1, initializing iteration times t, and taking the initial load adjustment efficiency value of each electric heating load as the load adjustment efficiency value of each electric heating load in the t iteration;
s2, substituting the load regulation efficiency values of the electric heating loads of the t iteration into a dual model of the load regulation efficiency optimization model, and solving the dual model to obtain load regulation quantity of the electric heating loads of the t iteration;
s3, correcting the load distribution quantity of each electric heating load of the t iteration according to the load adjustment quantity of each electric heating load of the t iteration;
s4, substituting the corrected load distribution amount of each electric heating load of the t iteration into a load regulation efficiency optimization model to obtain load regulation efficiency values of each electric heating load of the t +1 iteration;
s5. if βj,t+1-βj,tIf | ≧ βj,t＝βj,t+1And S2 is executed, otherwise, the load adjustment quantity of each electric heating load of the t iteration obtained by solving the dual model is used as the optimal load adjustment scheme, wherein βj,tAdjusting the efficiency rate for the load of the jth electric heating load for the tth iteration, βj,t+1The efficiency value is adjusted for the load of the jth electric heating load for the t +1 th iteration to be constant.
11. The apparatus of claim 7 or 10, wherein the dual model of the load regulation efficiency optimization model is determined as follows:
Figure FDA0002491314530000051
in the formula urWeight coefficient for the r-th expected yield, viThe weight factor invested for the ith resource,
Figure FDA0002491314530000052
Figure FDA0002491314530000053
w is an unconstrained variable which is a variable,
Figure FDA0002491314530000054
Δ B is the load regulation target amount, Δ BjLoad regulation for jth electric heating load, a1Is a first decision parameter, a2Is the second decision parameter.
12. The apparatus of claim 10, wherein the modifying the load distribution of the electric heating loads for the tth iteration based on the load adjustment of the electric heating loads for the tth iteration comprises:
determining the average value of the load adjustment quantity of all the electric heating loads in the t iteration according to the load adjustment quantity of each electric heating load in the t iteration
Figure FDA0002491314530000055
Based on
Figure FDA0002491314530000056
And correcting the load distribution quantity of each electric heating load of the t iteration according to the following formula:
Figure FDA0002491314530000057
in the formula, bj,tFor the t-th iterationLoad distribution amount of j electric heating loads, b'j,tAnd the load distribution quantity of the jth electric heating load is iterated for the corrected tth time.
CN202010406056.2A 2020-05-14 2020-05-14 Electric heating load adjustment optimization method and device Pending CN111668851A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113124451A (en) * 2021-04-21 2021-07-16 哈尔滨工业大学 Electric load grading optimization capacity-increasing-free control system and method for coal-to-electric heating
CN116247682A (en) * 2023-05-08 2023-06-09 国网辽宁省电力有限公司 Method and device for regulating and controlling load of power distribution network participating in heat accumulating type electric heating and storage medium

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113124451A (en) * 2021-04-21 2021-07-16 哈尔滨工业大学 Electric load grading optimization capacity-increasing-free control system and method for coal-to-electric heating
CN113124451B (en) * 2021-04-21 2022-10-04 哈尔滨工业大学 Electric load grading optimization capacity-increase-free control system and method for coal-to-electric heating
CN116247682A (en) * 2023-05-08 2023-06-09 国网辽宁省电力有限公司 Method and device for regulating and controlling load of power distribution network participating in heat accumulating type electric heating and storage medium
CN116247682B (en) * 2023-05-08 2023-07-25 国网辽宁省电力有限公司 Method and device for regulating and controlling load of power distribution network participating in heat accumulating type electric heating and storage medium

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