CN109544016A - A kind of smart grid scheduling system and dispatching method based on user demand - Google Patents
A kind of smart grid scheduling system and dispatching method based on user demand Download PDFInfo
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Abstract
The invention discloses a kind of, and the smart grid based on user demand dispatches system, including multiple subscriber units, multiple generator units, multiple cogeneration units, multiple boiler units and main power grid;The subscriber unit includes electrical equipment or electric appliance, photovoltaic generating module, wind power generation module, electric car;Cogeneration unit externally exports electric energy and external heat supply using natural gas as raw material, and the heat supply and power supply of cogeneration unit are located in feasible operation interval;Boiler unit is using natural gas as raw material, external heat supply.The invention also provides a kind of dispatching methods, for intelligence computation module by accelerating intelligent algorithm to select subscriber unit, generator unit, cogeneration unit, boiler unit, the purchase sale of electricity of main power grid and purchase gas strategy, each unit, main power grid carry out distributed purchase sale of electricity transaction, heat supply transactions through block catenary system.The present invention sets price driven mechanism, promotes the consumption of generation of electricity by new energy, and effectively increases the reliability of operation of power networks.
Description
Technical field
The invention belongs to dispatching of power netwoks fields, and in particular to a kind of smart grid scheduling system and tune based on user demand
Degree method.
Background technique
In recent years, as new energy power generation technology is grown rapidly, application is throughout to every family.Although increasingly
More places starts to be laid out distributed new electricity generation system, but since the uncertain factors such as itself and weather, weather are closely related,
It causes new energy power generation technology to there is significantly randomness, prestige is caused to the reliability service of power grid after in turn resulting in new-energy grid-connected
The side of body;Since its randomness is big, fluctuation of service, generation of electricity by new energy is also not public receiving and consumption, abandons electricity and happens occasionally.Separately
Outside, since user is to the opacity of power generation situation, cause user can not the reasonable arrangement electricity consumption time, when causing load end electricity consumption
Between concentrate, biggish impact is caused to power grid.It can integrate and solve the above problems there are no technological means in the prior art.In addition,
Traditional power grid is using the monitoring method of centralization, and not only unfavorable to its reliability operation, the power information needs of user are sent to
Centralized supervisory and control equi be easy to cause privacy of user leakage problem.
It can be seen that there are users to concentrate electricity consumption, privacy of user leakage for the prior art, the electricity of generation of electricity by new energy is difficult for
Masses receive and the technical problems such as consumption.
Summary of the invention
Present invention aim to address the above problems, provide a kind of smart grid scheduling system based on user demand, electricity
Valence market allotment mechanism and payments mechanism pass through block catenary system and complete, and the electricity demand of each user uses heat demand amount
And power generation measurer is measured or is predicted by intelligence instrument;By the distributed book keeping operation function of block chain module, or by intelligence
The store function and information exchange function of energy computing module, record the acquired information of intelligence instrument, are based on these information, lead to
Each distributed intelligence computing module is crossed by the super excess calculation of the surplus of each user's generated energy or demand and is sent to
Each corresponding block chain metering units of user, while the power generation of each user and demand data being stored in and corresponding area
In storage unit in block chain metering units, or directly above-mentioned data are stored in intelligence computation module, as local letter
Breath.It can preferably protect that each user's is hidden while allowing power grid to make power supply, electric generation management in real time by this kind of mode
Personal letter breath.Wherein, the network topology of each distributed intelligence computing module composition is connection.For a user, according to electricity
Valence, combustion gas valence carry out power scheduling, consistent with generator unit, cogeneration unit interests dispatch action to take.
The technical scheme is that a kind of smart grid based on user demand dispatches system, including multiple users list
First, multiple generator units, multiple cogeneration units and multiple boiler units, the subscriber unit, generator unit, cogeneration of heat and power
Unit is connect with main power grid respectively, can be introduced from main power grid or be conveyed electric energy to it;The subscriber unit include electrical equipment or
Electric appliance, intelligence instrument, photovoltaic generating module, wind power generation module, electric car, intelligence instrument measure subscriber unit generated energy and
Electricity, the heat of consumption, and predict the electricity demand of user, heat demand amount;Cogeneration unit using natural gas as raw material,
Externally output electric energy and external heat supply, the heat supply and power supply of cogeneration unit are located in feasible operation interval;Boiler unit
Using natural gas as raw material, external heat supply.
The smart grid scheduling system based on user demand further includes calculating and memory module, is calculated and memory module
Including multiple intelligence computation modules, the intelligence computation module is based on electricity price, combustion gas valence, conveying cost, distributed network, distribution
The electricity that subscriber unit is bought or sold from main power grid is calculated likes, is bought from each cogeneration unit or boiler unit
Heat, and purchase sale of electricity instruction, transmission of electricity instruction and heat supply instruction are formed, it sends corresponding unit to, is heated in subscriber unit without electricity
Equipment is heated using centralized system, and the electricity that subscriber unit is bought is only used for non-heat demand, and the heat demand of subscriber unit passes through
Boiler unit heat supply or cogeneration unit meet, the heating load and electricity bought from each cogeneration unit, from power generation
Unit buys electricity, and heat is bought from boiler unit, in scheduling phase a few days ago, by intelligence computation module, select power purchase and
Gas strategy is purchased, is guaranteed systematically with the maximized working method operation of economic interests;During real time execution, based on timesharing electricity
Valence formulates the use period planning of electric appliance or electrical equipment for user, guarantees user with economic interests by intelligence computation module
Maximized mode uses the time plan each electric appliance or electrical equipment.
A kind of dispatching method of the smart grid scheduling system based on user demand, the number of distributed intelligence computing module
With equal, each intelligence computation of the sum of subscriber unit, generator unit, cogeneration unit, the number of boiler unit and main power grid
The corresponding subscriber unit of module or generator unit or cogeneration unit or boiler unit or main power grid, and recognized by block chain
It demonstrate,proves, the electricity transaction, heat supply between unit or between unit and main power grid carry out simultaneously record storage through block catenary system, logical
Cross purchase electricity sales amount information between block catenary system acquiring unit or between unit and main power grid, heat information provision, thermoelectricity
The purchase tolerance information of cogeneration unit, boiler unit;By each intelligence computation module composition distributed network, the distributed network pair
The network topology answered is connection, communication of equal value between the intelligence computation module of connection;The heat demand of subscriber unit is by thermoelectricity
Cogeneration unit, boiler unit supply, are preferentially supplied by cogeneration unit;In scheduling phase a few days ago, the intelligence computation module
By accelerate intelligent algorithm select subscriber unit, generator unit, cogeneration unit, boiler unit, main power grid purchase sale of electricity and
Purchase gas strategy, the acceleration intelligent algorithm specifically includes the following steps:
(1) the intelligence computation module respectively from block catenary system authenticate, obtain other intelligence computation modules calculating from
Other users unit, generator unit, cogeneration unit, main power grid purchase of electricity information, purchase tolerance information and to other units or
The electricity sales amount information of main power grid, the heat demand of subscriber unit;
(2) each intelligence computation module corresponds to the purchase of electricity information obtained based on it, purchases tolerance information and electricity sales amount information,
It calculates and stores corresponding collaborative parameters;
(3) each intelligence computation module corresponds to the purchase of electricity information obtained based on it, purchases tolerance information and electricity sales amount information
And the last resulting corresponding collaborative parameters of calculating, current corresponding electricity price and combustion gas valence, it calculates and stores corresponding purchase
Information about power purchases tolerance information and electricity sales amount information;
(4) whether the difference of the purchase electricity sales amount, purchase tolerance that judge intelligence computation module twice adjacent calculation no more than sets
Determine threshold value;
(4a) is if the purchase electricity sales amount of twice adjacent calculation, the difference of purchase tolerance are no more than given threshold, each intelligence meter
Purchase electricity sales amount, the purchase tolerance information that module submits intelligence computation module to calculate to block catenary system are calculated, is executed step (5);
(4b) returns to step (1) if the purchase electricity sales amount of twice adjacent calculation or the difference for purchasing tolerance are more than given threshold;
(5) each subscriber unit, generator unit, cogeneration unit, boiler unit, main power grid are distributed from block catenary system
Formula obtains its corresponding last time and calculates gained purchase of electricity information, purchases tolerance information and electricity sales amount information, and be based on the letter
Breath carries out power generation and the production of heat supply thermal energy;
(6) each unit carries out distributed purchase sale of electricity transaction, heat supply transactions through block catenary system, carry out electricity supply,
Heat supply.
The step (2) specifically includes the following steps:
(2a) successively numbers multiple subscriber units, multiple generator units, multiple cogeneration units, multiple boiler units
The N that is 1,2 ... numbers main power grid for N+1, and wherein N is subscriber unit, generator unit, cogeneration unit, boiler unit
The sum of number;Unit i, i=1,2 ... the N+1 that (2b) is i for number, when it is subscriber unit or generator unit or thermoelectricity connection
When producing unit, the electricity collaborative parameters of its corresponding intelligence computation module i are iterated to calculate by following formula,
WhereinResulting collaborative parameters value, g are calculated for unit i kth timeiFor the current generated energy of unit i, diFor unit i
Current power demand,The charge value that resulting unit i is sold to unit j is calculated for kth time,Gained is calculated for kth time
The charge value sold to unit i of unit j, selected electricity collaborative parameters when calculating for the first timeInitial value
(2C) for unit i, when it is cogeneration unit or boiler unit, corresponding intelligence computation module i passes through
Following formula iterates to calculate its heat collaborative parameters,
WhereinResulting heat collaborative parameters are calculated for kth time, h is the sum of the heat demand of each unit,For kth time
The purchase tolerance of resulting unit i is iterated to calculate, wherein aiIt is imitated for corresponding cogeneration unit or the energy conversion of boiler unit
Rate, the initial value of selected heat collaborative parameters when calculating for the first time
The step (3) specifically includes following steps,
(3a) establishes performance index function c according to current electricity price, combustion gas valence, for characterizing the investment consumption of power grid,
Wherein pijIt is unit i or main power grid to unit j or the electricity price of main power grid sale of electricity;If unit i or unit j is boiler list
Member, then pij=0;niThe gas price of natural gas, s are bought for unit iiTo purchase tolerance;
(3b) is updated for unit i, by its corresponding intelligence computation module i by following formula iteration
Wherein, argmin { } expression makes function in braces obtain the smallest corresponding xijAnd siValue, α, β be often system
Number,The charge value that resulting unit i is sold to unit j is calculated for kth step, selected initial value when calculating for the first timeWith
It is related to the generator unit of solar power generation or wind-power electricity generation to the sale of electricity price p of other unit sales of electricityijLower than not
It is related to the generator unit of solar power generation or wind-power electricity generation to the sale of electricity price p of other unit sales of electricityji。
Beneficial effects of the present invention:
(1) information exchange, subscriber unit, generator unit, thermoelectricity are carried out by using block catenary system, intelligence computation module
Cogeneration unit, boiler unit can carry out information exchange, thus its discovery and biography outwardly when failure occurs between any two
It send and is more easier, to greatly enhance the reliability of power grid.Simultaneously as the state of unit can quickly be transferred to block chain
System and corresponding intelligence computation module can carry out fault diagnosis using intelligence computation module faster, to accelerate event
Hinder diagnosis efficiency, to enhance the reliability of power grid.Intelligence computation module can be sent in real time by network to faulty unit
Instruction, for debugging so that power system restoration is normal, to accelerate trouble shooting procedure.
(2) dispatching method based on intelligence computation module, the purchase sale of electricity information of user, electricity consumption timetable is without useful in institute
It is directly transmitted between family, to preferably protect the privacy of user.
(3) dispatching method based on intelligence computation module saves labor without the scheduling a few days ago of artificial progress electricity market
Dynamic resource;
(4) effectively enhance the reliability of operation of power networks.Since user can be power generation end, electricity consumption end can be, it can also be with
It is both power generation end and user terminal, so that the flexible dispatching of electric power can be realized, reduces conveying distance, power generation and power consumption efficiency obtain
It is promoted.By the electrical allotment of electric system, the utilization efficiency of the energy can be improved.
(5) price driven, incentive mechanism are set, the consumption of generation of electricity by new energy is promoted.
(6) by intelligence computation module, power purchase and purchase can be selected under the premise of protecting user and power generation end data privacy
Gas strategy, and period planning is used for user's formulation electric appliance, the cost and CO2 emission at power generation end are both reduced, is also made
User participates in dispatching by reasonable arrangement electric appliance using the time simultaneously, further reaches to reduce and imitate to the technology that power grid impacts
Fruit;Meanwhile the combination of both technological means also can rationally reduce the electric cost of user.I.e. by intelligence computation module come for
Generate electricity end, heat supply end selection power purchase and purchase gas strategy, and uses period planning for user's formulation electric appliance, can play to power generation
End, heat supply end, user bring economic benefit, and further enhance the technical effect of electric network reliability.
(7) using the intelligent accelerating algorithm selection power purchase and purchase gas strategy proposed in the present invention, it is ensured that entire decision
The reliability of process.Although the power load of load side is time-varying in real-time electric power scheduling process, but as long as its variation speed
Rate is lower than the calculating convergence rate proposed by the present invention for accelerating intelligent algorithm, when which can handle these in real time
Varying duty, to ensure that the reliability of power scheduling process.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples.
Fig. 1 is physical connection schematic diagram of the invention.
Fig. 2 is information connection schematic diagram of the invention.
Fig. 3 is the flow diagram of dispatching method of the invention.
Specific embodiment
Embodiment one
As shown in Figure 1 and Figure 2, a kind of smart grid based on user demand dispatches system comprising: it is several to be with family
The subscriber unit of unit, several generator units, several cogeneration units, several boiler modules;Subscriber unit, generator unit,
Cogeneration unit is connect with main power grid respectively, can be introduced from main power grid or be conveyed electric energy to it.Wherein as unit of family
Subscriber unit includes household electrical appliance, such as refrigerator, washing machine, dish-washing machine, electric light, television set, further includes intelligence instrument, photovoltaic hair
Electric module, wind power generation module and electric car, intelligence instrument measure electricity, the heat of subscriber unit generated energy and consumption, and
Predict electricity demand, the heat demand amount of user;Cogeneration unit can externally export electric energy and right using natural gas as raw material
Outer heat supply, the heat supply and power supply of cogeneration unit are located in feasible operation interval;Boiler unit is right using natural gas as raw material
Outer heat supply.
Smart grid scheduling system based on user demand further includes calculating and memory module, and calculating includes with memory module
Several distributed computing modules, distributed computing module are used for based on electricity price, combustion gas valence, conveying cost, distributed network, distribution
The electricity each bought or sold from regional power grid as the subscriber unit of unit using family is calculated likes, from each cogeneration of heat and power
The heating load that unit or boiler unit are bought, and power purchase/transmission of electricity instruction and heat supply instruction are formed, send corresponding domestic consumer to
Unit.Without electric heating equipment in domestic consumer's unit, heated using centralized system, wherein the electricity bought be only used for it is non-in family
Heat demand, heat demand are met by boiler heat supplying or co-generation unit, the confession bought from each cogeneration unit
Heat and electricity, buy heat from boiler unit, in scheduling phase a few days ago, by distributed computing module, select power purchase and
Gas strategy is purchased, is guaranteed systematically with the maximized working method operation of economic interests;During real time execution, based on timesharing electricity
Valence formulates the period planning that uses of electric appliance for user by distributed computing module, and guarantee user is maximized with economic interests
Mode come plan each electric appliance use the time.Through the above scheme, the energy equilibrium of supply and demand of entire power grid is met.It is combined
The energy of each user exceeds and is short of, and by distributed arithmetic, obtains optimum instruction, issues control instruction, control each use
The power generation and transmission of electricity at family.
It include using family as several power generations of unit and electricity consumption module, several electricity generation modules, several cogenerations of heat and power in system
Unit.Wherein using family to include household electrical appliance, such as refrigerator, washing machine, dish-washing machine etc. and can be again in the subscriber unit of unit
Raw energy electricity generation module, such as photovoltaic generating module, wind power generation module etc..Cogeneration unit, can be right using natural gas as raw material
Outer output electric energy and external heating and cooling, the heating and cooling of cogeneration unit and power supply are located in feasible operation interval,
The waste heat that power generation waste heat, cooling supply generate both participates in the transaction of block chain, carries out electric-gas scheduling by block chain, promotes the energy
Multiple dimensioned calling.When carrying out power scheduling, when electricity is inadequate, power scheduling is carried out according to following priority: first being met
Then the power demand of strategic user meets the power demand of other users.
Preferably, equipped with thermomotor, photovoltaic, wind-power electricity generation, electric car and elastic load etc. in subscriber unit.
Preferably, further include carbon dioxide certification link in distributed computing module, and include titanium dioxide in optimization aim
Carbon emission index can not only optimize cost control, can also promote making for clean energy resource by minimizing total economic indicator
With.
As shown in figure 3, the dispatching method of the smart grid scheduling system employed in the present embodiment based on user demand,
The number of distributed computing module and subscriber unit, generator unit, cogeneration unit, the number of boiler unit and main power grid it
With equal, the corresponding subscriber unit of each intelligence computation module or generator unit or cogeneration unit or boiler unit or master
Power grid, and authenticated by block chain, it is obtained from corresponding subscriber unit, generator unit, cogeneration unit from other use
Family unit, generator unit, cogeneration unit, main power grid purchase of electricity information, purchase tolerance information and to other users unit, main electricity
Net sells the information of electricity;By each distributed computing module composition distributed network, the corresponding network of the distributed network is opened up
It flutters as connection, communication of equal value between the distributed computing module of connection.
In scheduling phase a few days ago, distributed computing module by accelerate intelligent algorithm select each subscriber unit, generator unit,
The power purchase of cogeneration unit and purchase gas strategy, accelerate intelligent algorithm specifically includes the following steps:
(1) distributed computing module is authenticated from block chain respectively, from corresponding subscriber unit, generator unit, cogeneration of heat and power
Obtained in unit previous step calculate it is resulting its from other users unit, generator unit, cogeneration unit, main power grid purchase of electricity
Information purchases tolerance information and sells the electricity sales amount information of electricity, the heat demand of each user to other users unit, main power grid;
(2) each distributed computing module corresponds to the purchase of electricity information obtained based on it, purchases tolerance information and electricity sales amount letter
Breath, calculates and stores corresponding collaborative parameters.For each user, when generated energy is greater than user power utilization demand, collaboration ginseng
Several values increases, and electric energy can externally be exported by representing it;When generated energy is less than user demand, which reduces, generation
Table its can dissolve electric energy;
(3) each distributed computing module corresponds to the purchase of electricity information obtained based on it, purchases tolerance information and electricity sales amount letter
Breath and previous step calculate resulting corresponding collaborative parameters, and current corresponding electricity price is calculated and deposited using intelligent algorithm is accelerated
Corresponding purchase of electricity information is stored up, tolerance information and electricity sales amount information are purchased;
(4) step (1)-(3) are repeated, until the resulting purchase of electricity information of twice adjacent calculation, purchase tolerance information and sale of electricity
The difference measured between information is no more than given threshold;
(5) its is corresponding most for Distributed Acquisition from block catenary system for each subscriber unit, generator unit, cogeneration unit
Once calculate resulting purchase of electricity information afterwards, purchase tolerance information and electricity sales amount information, and based on the information carry out power generation,
The production of heat supply thermal energy;
(6) each unit carries out distributed purchase sale of electricity transaction, heat supply transactions through block catenary system, carry out electricity supply,
Heat supply.Preferably.
Preferably, include following sub-step in step (2):
(2a) successively by subscriber unit, generator unit, cogeneration unit number be 1,2 ... N, by main power grid number be
N+1, wherein N is the sum of subscriber unit, generator unit, cogeneration unit, the number of boiler unit;
(2b) is for unit i, when it is subscriber unit or generator unit or cogeneration unit, corresponding distribution
Computing module i iterates to calculate its electricity collaborative parameters by following formula,
WhereinResulting collaborative parameters value, g are calculated for unit i kth timeiFor the current generated energy of unit i, diFor unit i
Current power demand,The charge value that resulting unit i is sold to unit j is calculated for kth time,Gained is calculated for kth time
The charge value sold to unit i of unit j, selected electricity collaborative parameters when calculating for the first timeInitial value
(2c) for unit i, when it is cogeneration unit or boiler unit, corresponding distributed computing module i is logical
It crosses following formula and iterates to calculate its heat collaborative parameters,
WhereinResulting heat collaborative parameters are calculated for kth time, h is the sum of the heat demand of each unit,For kth time
The purchase tolerance of resulting unit i is iterated to calculate, wherein aiIt is imitated for corresponding cogeneration unit or the energy conversion of boiler unit
Rate, the initial value of selected heat collaborative parameters when calculating for the first time
It preferably, include following sub-step in step (3),
(3a) establishes performance index function c according to current electricity price, combustion gas valence, for characterizing the investment consumption of power grid are as follows:
Wherein pijTo number the unit for being i or main power grid to the number unit for being j or the electricity price of main power grid sale of electricity;If number
The unit that unit or number for i are j corresponds to boiler module, then pij=0;niFor the gas price for the unit that number is i, si
To purchase tolerance;(3b) is updated for unit i, by its corresponding intelligence computation module i by following formula iteration
Wherein, argmin { } expression makes function in braces obtain the smallest corresponding xijAnd siValue, α, β be often system
Number,The charge value that resulting unit i is sold to unit j is calculated for kth step, selected initial value when calculating for the first timeWith
Preferably, generator unit when being related to solar power generation unit or wind power generation unit is to other unit sales of electricity
Sale of electricity price pijLower than the unit for not being related to solar power generation unit or wind power generation unit power generation to other unit sales of electricity
Sale of electricity price pji。
Preferably, collaborative parametersInitial value, collaborative parametersInitial value,Initial value andInitial value can be optional.
It preferably, will when each unit cannot all be connect with main power grid, cannot be introduced to main power grid or be conveyed electric energy to it
Step (2a) substitution are as follows:
Subscriber unit, generator unit, cogeneration unit, boiler unit number are successively 1,2 by (2a1) ... N, wherein
N is the sum of subscriber unit, generator unit, cogeneration unit, the number of boiler unit;
Step (3a) is substituted are as follows:
(3a1) establishes performance index function c according to current electricity price, combustion gas valence, for characterizing the investment consumption of power grid are as follows:
Wherein pijTo number the unit for being i or main power grid to the number unit for being j or the electricity price of main power grid sale of electricity;If number
The unit that unit or number for i are j corresponds to boiler module, then pij=0;niFor the gas price for the unit that number is i, si
To purchase tolerance;In general, through the invention it is contemplated above technical scheme is compared with the prior art, can obtain down and show
Beneficial effect:
(1) information exchange is carried out by using block catenary system, user is equivalent to energy subnet, can carry out between user
Information exchange, thus its discovery and transmission outwardly are more easier when failure occurs, so that greatly enhance power grid can
By property.Simultaneously as the state of user can quickly be transferred to block catenary system, failure can be carried out faster using the module
Diagnosis, so that efficiency of fault diagnosis is accelerated, to enhance the reliability of power grid.Block catenary system or distributed computing module can
Instruction is sent in real time to faulty user by network, for debugging so that power system restoration is normal, to accelerate event
Hinder maintenance process.
(2) dispatching method by above-mentioned based on block catenary system, distributed computing module, the power generation letter of domestic consumer
Breath, electricity consumption timetable need not directly transmit between all users, to preferably protect the privacy of user.
(3) dispatching method by above-mentioned based on block catenary system, distributed computing module, without artificial carry out electric power
Labo r resources are saved in the scheduling a few days ago in market;
(4) effectively enhance the reliability of operation of power networks.Since user can be power generation end, electricity consumption end can be, it can also be with
It is both power generation end and user terminal, for example has the home unit of renewable energy system, so that the spirit of electric power can be realized
Scheduling living, reduces conveying distance, and power generation and power consumption efficiency get a promotion.By the electrical allotment of electric system, energy can be improved
The utilization efficiency in source.
(5) price driven mechanism is set, the consumption of generation of electricity by new energy is promoted.
It (6), can be in protection user and the premise for the end data privacy that generates electricity by block catenary system, distributed computing module
Under, power purchase and purchase gas strategy are selected, and use period planning for user's formulation electric appliance, both reduces the cost and two at power generation end
Carbon emission is aoxidized, user is also made to participate in dispatching using the time by reasonable arrangement electric appliance simultaneously, further reaches reduction pair
The technical effect of power grid impact;Meanwhile the combination of both technological means also can rationally reduce the electric cost of user.That is, logical
Cross block catenary system, distributed computing module to select power purchase and purchase gas strategy for power generation end, heat supply end, and formulates electricity for user
Device uses period planning, can play and bring economic benefit to power generation end, heat supply end, user, and further enhancing power grid can
By the technical effect of property.
(7) using the acceleration intelligent algorithm selection power purchase of middle proposition of the invention and purchase gas strategy, it is ensured that entirely certainly
The reliability of plan process.Although the power load of load side is time-varying in real-time electric power scheduling process, but as long as it changes
Rate can be implemented to handle these lower than the calculating convergence rate proposed by the present invention for accelerating intelligent algorithm, the acceleration intelligent algorithm
When varying duty, to ensure that the reliability of power scheduling process.
Embodiment two
As shown in Figure 1 and Figure 2, smart grid in the present embodiment based on user demand dispatches system comprising: it is several with
Family is the subscriber unit of unit, several generator units, several cogeneration units, several boiler units, subscriber unit, power generation
Unit, cogeneration unit, boiler unit are connect with main power grid respectively, can be introduced from main power grid or be conveyed electric energy to it.Wherein
It include household electrical appliance in user as unit of family, such as refrigerator, washing machine, dish-washing machine, electric light, television set further include intelligence
Energy instrument, photovoltaic generating module, wind power generation module and electric car, intelligence instrument measure subscriber unit generated energy and consumption
Electricity, heat, and predict the electricity demand of user, heat demand amount;Cogeneration unit, can be external using natural gas as raw material
Electric energy and external heat supply are exported, the heat supply and power supply of cogeneration unit are located in feasible operation interval;Boiler unit is with day
Right gas is raw material, external heat supply.
Smart grid scheduling system based on user demand further includes calculating and memory module, and calculating includes with memory module
Several intelligence computation modules, intelligence computation module is used for based on electricity price, combustion gas valence, conveying cost, wireless communication networks, distributed
Ground calculates the electricity each bought or sold from regional power grid as the power generation of unit and power unit using family, from each thermoelectricity
The heating load that cogeneration unit or boiler unit are bought, and power purchase/transmission of electricity instruction and heat supply instruction are formed, send corresponding family to
Subscriber unit.It without electric heating equipment in domestic consumer's unit, is heated using centralized system, wherein the electricity bought is only used in family
Non- heat demand, heat demand met by boiler heat supplying or co-generation unit, bought from each cogeneration of heat and power module
Heating load and electricity, buy heat from boiler unit, in scheduling phase a few days ago, by intelligence computation module, select power purchase and
Gas strategy is purchased, is guaranteed systematically with the maximized working method operation of economic interests;During real time execution, based on timesharing electricity
Valence formulates the period planning that uses of electric appliance for user by intelligence computation module, and guarantee user is maximumlly square with economic interests
Formula come plan each electric appliance use the time.
Through the above scheme, the energy equilibrium of supply and demand of entire power grid is met.It combines the energy of each user to exceed
And shortcoming obtains optimum instruction by distributed arithmetic, issues control instruction, controls the power generation and transmission of electricity of each user.
When carrying out power scheduling, when electricity is inadequate, power scheduling is carried out according to following priority: first meeting strategy
The power demand of property user, then meets the power demand of other users.
Preferably, equipped with thermomotor, photovoltaic, wind-power electricity generation, electric car and elastic load etc. in family.
Preferably, further include carbon dioxide certification link in intelligence computation module, and include carbon dioxide in optimization aim
Discharge index can not only optimize cost control, can also promote making for clean energy resource by minimizing total economic indicator
With.
As shown in figure 3, the dispatching method of the smart grid scheduling system used by the present embodiment based on user demand, intelligence
Can computing module number and equal, the Mei Gezhi of the sum of subscriber unit, generator unit, cogeneration unit, the number of main power grid
The corresponding subscriber unit of energy computing module or generator unit or cogeneration unit or boiler unit or main power grid, each intelligence meter
Calculating module is wireless telecommunications connection, i.e., can transmit information by wireless telecommunications between any two intelligence computations module.A few days ago
Scheduling phase, intelligence computation module is by accelerating intelligent algorithm to select each subscriber unit, each generator unit, each cogeneration unit
Power purchase and purchase gas strategy, accelerate intelligent algorithm specifically includes the following steps:
(1) several computing modules pass through communication network from corresponding subscriber unit, generator unit, cogeneration of heat and power respectively
Obtained in unit previous step calculate it is resulting its from other users unit, generator unit, cogeneration unit, main power grid purchase of electricity
Information purchases tolerance information and sells the electricity sales amount information of electricity to other users unit, main power grid, and the heat of each subscriber unit needs
It asks;
(2) each intelligence computation module corresponds to the purchase of electricity information obtained based on it, purchases tolerance information and electricity sales amount information,
It calculates and stores corresponding collaborative parameters;
(3) each intelligence computation module corresponds to the purchase of electricity information obtained based on it, purchases tolerance information and electricity sales amount information
And previous step calculates resulting corresponding collaborative parameters, current corresponding electricity price calculates and stores corresponding purchase of electricity information,
Purchase tolerance information and electricity sales amount information;
(4) step (1)-(3) are repeated, until the resulting purchase of electricity information of twice adjacent calculation, purchase tolerance information and sale of electricity
The difference measured between information is no more than given threshold;
(5) each subscriber unit, generator unit, cogeneration unit, the boiler unit distribution from intelligence computation module obtain
It takes its corresponding last time to calculate resulting purchase of electricity information, purchases tolerance information and electricity sales amount information, and be based on the information
Carry out power generation, the production of heat supply thermal energy;
(6) each subscriber unit, generator unit, cogeneration unit, boiler unit carry out electricity supply, heat supply.
Preferably, include following sub-step in step (2):
Subscriber unit, generator unit, cogeneration unit number are successively 1,2 by (2a) ... N;It is by main power grid number
N+1;Wherein N is the sum of subscriber unit, generator unit, cogeneration unit, the number of boiler unit;
(2b) is for unit i, when it is subscriber unit or generator unit or cogeneration unit, corresponding distribution
Computing module i iterates to calculate its electricity collaborative parameters by following formula,
WhereinResulting collaborative parameters value, g are calculated for unit i kth timeiFor the current generated energy of unit i, diFor unit i
Current power demand,The charge value that resulting unit i is sold to unit j is calculated for kth time,Gained is calculated for kth time
The charge value sold to unit i of unit j, selected electricity collaborative parameters when calculating for the first timeInitial value
(2c) for unit i, when it is cogeneration unit or boiler unit, corresponding distributed computing module i is logical
It crosses following formula and iterates to calculate its heat collaborative parameters,
WhereinResulting heat collaborative parameters are calculated for kth time, h is the sum of the heat demand of each unit,For kth time
The purchase tolerance of resulting unit i is iterated to calculate, wherein aiIt is imitated for corresponding cogeneration unit or the energy conversion of boiler unit
Rate, the initial value of selected heat collaborative parameters when calculating for the first time
Preferably, include following sub-step in step (3):
(3a) establishes performance index function c according to current electricity price, combustion gas valence, for characterizing the investment consumption of power grid are as follows:
Wherein pijTo number the unit for being i or main power grid to the number unit for being j or the electricity price of main power grid sale of electricity;If number
The unit that unit or number for i are j corresponds to boiler module, then pij=0;niFor the gas price for the unit that number is i, si
To purchase tolerance;(3b) is updated for unit i, by its corresponding intelligence computation module i by following formula iteration
Wherein, argmin { } expression makes function in braces obtain the smallest corresponding xijAnd siValue, α, β be often system
Number,The charge value that resulting unit i is sold to unit j is calculated for kth step, selected initial value when calculating for the first timeWith
Preferably, it is related to the generator unit of solar power generation or wind-power electricity generation to the sale of electricity price p of other unit sales of electricityij
Lower than not being related to the generator unit of solar power generation or wind-power electricity generation to the sale of electricity price p of other unit sales of electricityji。
Preferably, electricity collaborative parametersInitial value, heat collaborative parametersInitial value,Initial value andInitial value can be optional.
It preferably, will when each unit cannot all be connect with main power grid, cannot be introduced from main power grid or be conveyed electric energy to it
Step (2a) substitution are as follows:
Subscriber unit, generator unit, thermoelectron coproduction module number are successively 1,2 by (2a1) ... N, wherein N is user
The sum of unit, generator unit, cogeneration unit, number of boiler unit;
Step (3a) is substituted are as follows:
(3a1) establishes performance index function c according to current electricity price, combustion gas valence, for characterizing the investment consumption of power grid are as follows:
Wherein pijTo number the unit for being i or main power grid to the number unit for being j or the electricity price of main power grid sale of electricity;If number
The unit that unit or number for i are j corresponds to boiler module, then pij=0;niFor the gas price for the unit that number is i, si
To purchase tolerance;In general, through the invention it is contemplated above technical scheme is compared with the prior art, can obtain down and show
Beneficial effect:
(1) by the information exchange between user, when failure occurs, its discovery and transmission outwardly are more easier, from
And greatly enhance the reliability of power grid.Simultaneously as the state of user can quickly be transferred to intelligence computation module, this is utilized
Module can carry out fault diagnosis faster, so that efficiency of fault diagnosis is accelerated, to enhance the reliability of power grid.
(2) labo r resources are saved without the scheduling a few days ago of artificial progress electricity market by above-mentioned dispatching method.
(3) effectively enhance the reliability of operation of power networks.Since user can be power generation end, electricity consumption end can be, it can also be with
It is both power generation end and user terminal, for example has the family of renewable energy system, so that the flexible tune of electric power can be realized
Degree, reduces conveying distance, and power generation and power consumption efficiency get a promotion.By the electrical allotment of electric system, the energy can be improved
Utilization efficiency.
(4) price driven mechanism is set, the consumption of generation of electricity by new energy is promoted.
(5) by intelligence computation module, power purchase and purchase gas strategy may be selected, and formulate counting using the time for electric appliance for user
It draws, both reduces the cost and CO2 emission at power generation end, also make user while passing through the use time of reasonable arrangement electric appliance
It participates in dispatching, further reaches the technical effect for reducing and impacting to power grid;Meanwhile the combination of both technological means can also close
Reason reduces the electric cost of user.That is, power purchase and purchase gas strategy are selected for power generation end, heat supply end by intelligence computation module,
And period planning is used for user's formulation electric appliance, it can play and bring economic benefit, Yi Jijin to power generation end, heat supply end, user
The technical effect of one step enhancing electric network reliability.
(6) using the acceleration intelligent algorithm selection power purchase of middle proposition of the invention and purchase gas strategy, it is ensured that entirely certainly
The reliability of plan process.Although the power load of load side is time-varying in real-time electric power scheduling process, but as long as it changes
Rate can be implemented to handle these lower than the calculating convergence rate proposed by the present invention for accelerating intelligent algorithm, the acceleration intelligent algorithm
When varying duty, to ensure that the reliability of power scheduling process.
Claims (5)
1. a kind of smart grid based on user demand dispatches system, which is characterized in that including multiple subscriber units, multiple power generations
Unit, multiple cogeneration units and multiple boiler units, the subscriber unit, generator unit, cogeneration unit respectively with
Main power grid connection, can introduce from main power grid or convey electric energy to it;The subscriber unit includes electrical equipment or electric appliance, photovoltaic hair
Electric module, wind power generation module, electric car;Cogeneration unit externally exports electric energy and externally supplies using natural gas as raw material
Heat, the heat supply and power supply of cogeneration unit are located in feasible operation interval;Boiler unit is externally supplied using natural gas as raw material
Heat;
The smart grid scheduling system based on user demand further includes calculating and memory module, and calculating includes with memory module
Multiple intelligence computation modules, the intelligence computation module are based on electricity price, combustion gas valence, conveying cost, distributed network, in a distributed manner
Calculate the electricity that subscriber unit is bought or sold from main power grid, the heat bought from each cogeneration unit or boiler unit
Amount, and purchase sale of electricity instruction, transmission of electricity instruction and heat supply instruction are formed, it sends corresponding unit to, is set in subscriber unit without electricity heating
It is standby, it is heated using centralized system, the electricity that subscriber unit is bought is only used for non-heat demand, and the heat demand of subscriber unit passes through pot
Furnace unit heating or cogeneration unit meet, and the heating load and electricity bought from each cogeneration unit are single from power generation
Member buys electricity, and heat is bought from boiler unit, selects power purchase and purchase by intelligence computation module in scheduling phase a few days ago
Gas strategy guarantees systematically with the maximized working method operation of economic interests;During real time execution, based on timesharing electricity
Valence formulates the use period planning of electric appliance or electrical equipment for user, guarantees user with economic interests by intelligence computation module
Maximized mode uses the time plan each electric appliance or electrical equipment.
2. using the dispatching method of the smart grid scheduling system described in claim 1 based on user demand, which is characterized in that
The number and subscriber unit, generator unit, cogeneration unit, boiler unit and main power grid of the distributed intelligence computing module
The sum of number it is equal, the corresponding subscriber unit of each intelligence computation module or generator unit or cogeneration unit or boiler
Unit or main power grid, and authenticated by block chain, electricity transaction, heat supply warp between unit or between unit and main power grid
Block catenary system carries out and record storage, is sold by the purchase between block catenary system acquiring unit or between unit and main power grid
Information about power, heat information provision, cogeneration unit, the purchase tolerance information of boiler unit;By each intelligence computation module composition
Distributed network, the corresponding network topology of the distributed network are connection, of equal value logical between the intelligence computation module of connection
Letter;The heat demand of subscriber unit is supplied by cogeneration unit, boiler unit, is preferentially supplied by cogeneration unit;
In scheduling phase a few days ago, the intelligence computation module is by accelerating intelligent algorithm to select subscriber unit, generator unit, thermoelectricity
Cogeneration unit, boiler unit, main power grid purchase sale of electricity and purchase gas strategy, the acceleration intelligent algorithm specifically includes the following steps:
(1) the intelligence computation module respectively from block catenary system authenticate, obtain other intelligence computation modules calculating from other
Subscriber unit, generator unit, cogeneration unit, main power grid purchase of electricity information purchase tolerance information and to other units or main electricity
The electricity sales amount information of net, the heat demand of subscriber unit;
(2) each intelligence computation module corresponds to the purchase of electricity information obtained based on it, purchases tolerance information and electricity sales amount information, calculates
And store corresponding collaborative parameters;
(3) each intelligence computation module corresponds to the purchase of electricity information obtained based on it, purchase tolerance information and electricity sales amount information and
Last time calculates resulting corresponding collaborative parameters, current corresponding electricity price and combustion gas valence, calculates and stores corresponding purchase of electricity
Information purchases tolerance information and electricity sales amount information,
(4) whether the purchase electricity sales amount for judging intelligence computation module twice adjacent calculation, the difference for purchasing tolerance no more than set threshold
Value;
(4a) is if the purchase electricity sales amount of twice adjacent calculation, the difference of purchase tolerance are no more than given threshold, each intelligence computation mould
Block submits the purchase electricity sales amount of intelligence computation module calculating, purchase tolerance information to block catenary system, executes step (5);
(4b) returns to step (1) if the purchase electricity sales amount of twice adjacent calculation or the difference for purchasing tolerance are more than given threshold;
(5) each subscriber unit, generator unit, cogeneration unit, boiler unit, main the power grid distribution from block catenary system obtain
Take its corresponding last time to calculate gained purchase of electricity information, purchase tolerance information and electricity sales amount information, and based on the information into
Row power generation and the production of heat supply thermal energy;
(6) each subscriber unit, generator unit, cogeneration unit, boiler unit, main power grid carry out distributed through block catenary system
Sale of electricity transaction, heat supply transactions are purchased, electricity supply, heat supply are carried out.
3. dispatching method according to claim 2, which is characterized in that the step (2) specifically includes the following steps:
Multiple subscriber units, multiple generator units, multiple cogeneration units, multiple boiler units number are successively 1 by (2a),
2 ... N number main power grid for N+1, and wherein N is subscriber unit, generator unit, cogeneration unit, the number of boiler unit
The sum of;
Unit i, i=1,2 ... the N+1 that (2b) is i for number, when it is subscriber unit or generator unit or cogeneration of heat and power list
When first, the electricity collaborative parameters of its corresponding intelligence computation module i are iterated to calculate by following formula,
WhereinResulting collaborative parameters value, g are calculated for unit i kth timeiFor the current generated energy of unit i, diFor working as unit i
Preceding power demand,The charge value that resulting unit i is sold to unit j is calculated for kth time,Resulting list is calculated for kth time
The charge value that first j is sold to unit i, selected electricity collaborative parameters when calculating for the first timeInitial value
(2C) for unit i, when it is cogeneration unit or boiler unit, corresponding intelligence computation module i passes through as follows
Formula iterates to calculate its heat collaborative parameters,
WhereinResulting heat collaborative parameters are calculated for kth time, h is the sum of the heat demand of each unit,For kth time iteration
The purchase tolerance of resulting unit i is calculated, wherein aiIt is first for corresponding cogeneration unit or the energy conversion efficiency of boiler unit
The initial value of heat collaborative parameters is selected when secondary calculating
4. dispatching method according to claim 3, which is characterized in that
The step (3) specifically includes following steps,
(3a) establishes performance index function c according to current electricity price, combustion gas valence, for characterizing the investment consumption of power grid,
Wherein pijIt is unit i or main power grid to unit j or the electricity price of main power grid sale of electricity;If unit i or unit j is boiler unit,
Then pij=0;niThe gas price of natural gas, s are bought for unit iiTo purchase tolerance;
(3b) is updated for unit i, by its corresponding intelligence computation module i by following formula iteration
Wherein, argmin { } expression makes function in braces obtain the smallest corresponding xijAnd siValue, α, β are constant coefficient,
The charge value that resulting unit i is sold to unit j is calculated for kth step, selected initial value when calculating for the first timeWith
5. dispatching method according to claim 4, which is characterized in that be related to the power generation of solar power generation or wind-power electricity generation
Sale of electricity price p of the unit to other unit sales of electricityijLower than be not related to the generator unit of solar power generation or wind-power electricity generation to its
The sale of electricity price p of his unit sale of electricityji。
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Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110969335A (en) * | 2019-08-20 | 2020-04-07 | 中国科学技术大学 | Distributed coordination method suitable for economic dispatching and demand response of smart power grid |
CN112381410A (en) * | 2020-11-16 | 2021-02-19 | 国网山东省电力公司莒县供电公司 | Power management method and system based on Internet of things block chain |
CN112396285A (en) * | 2020-09-24 | 2021-02-23 | 浙江大学 | Distributed data center computing power and energy source flow cooperative scheduling system and method |
CN113241800A (en) * | 2021-04-14 | 2021-08-10 | 中南大学 | Intelligent power grid control system based on regional electricity prices and control method thereof |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP2843788A2 (en) * | 2013-08-16 | 2015-03-04 | RWE Effizienz GmbH | Method for operating a power plant system |
WO2015031581A1 (en) * | 2013-08-28 | 2015-03-05 | Robert Bosch Gmbh | System and method for energy asset sizing and optimal dispatch |
CN104537435A (en) * | 2014-12-18 | 2015-04-22 | 国家电网公司 | Distributed power source optimizing configuration method based on user-side economic indexes |
CN107402556A (en) * | 2017-08-01 | 2017-11-28 | 华中科技大学 | A kind of intelligent home control system and its control method based on clean energy resource |
CN107612017A (en) * | 2017-08-09 | 2018-01-19 | 广西电网有限责任公司电力科学研究院 | Wind-electricity integration intelligent control system based on demand response and distributed energy storage |
-
2018
- 2018-11-27 CN CN201811426397.5A patent/CN109544016B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP2843788A2 (en) * | 2013-08-16 | 2015-03-04 | RWE Effizienz GmbH | Method for operating a power plant system |
WO2015031581A1 (en) * | 2013-08-28 | 2015-03-05 | Robert Bosch Gmbh | System and method for energy asset sizing and optimal dispatch |
CN104537435A (en) * | 2014-12-18 | 2015-04-22 | 国家电网公司 | Distributed power source optimizing configuration method based on user-side economic indexes |
CN107402556A (en) * | 2017-08-01 | 2017-11-28 | 华中科技大学 | A kind of intelligent home control system and its control method based on clean energy resource |
CN107612017A (en) * | 2017-08-09 | 2018-01-19 | 广西电网有限责任公司电力科学研究院 | Wind-electricity integration intelligent control system based on demand response and distributed energy storage |
Non-Patent Citations (1)
Title |
---|
顾伟 等: "含分布式电源和可调负荷的售电公司优化调度模型", 《电力***自动化》 * |
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110969335A (en) * | 2019-08-20 | 2020-04-07 | 中国科学技术大学 | Distributed coordination method suitable for economic dispatching and demand response of smart power grid |
CN112396285A (en) * | 2020-09-24 | 2021-02-23 | 浙江大学 | Distributed data center computing power and energy source flow cooperative scheduling system and method |
CN112396285B (en) * | 2020-09-24 | 2023-11-28 | 浙江大学 | Collaborative scheduling system and method for distributed data center calculation force and energy source flow |
CN112381410A (en) * | 2020-11-16 | 2021-02-19 | 国网山东省电力公司莒县供电公司 | Power management method and system based on Internet of things block chain |
CN112381410B (en) * | 2020-11-16 | 2022-09-23 | 国网山东省电力公司莒县供电公司 | Power management method and system based on Internet of things block chain |
CN113241800A (en) * | 2021-04-14 | 2021-08-10 | 中南大学 | Intelligent power grid control system based on regional electricity prices and control method thereof |
CN113241800B (en) * | 2021-04-14 | 2022-11-18 | 中南大学 | Intelligent power grid control system based on regional electricity prices and control method thereof |
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