CN109544016B - Intelligent power grid dispatching system and method based on user demands - Google Patents
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Abstract
The invention discloses a user demand-based intelligent power grid dispatching system, which comprises a plurality of user units, a plurality of power generation units, a plurality of cogeneration units, a plurality of boiler units and a main power grid, wherein the user units are connected with the main power grid through a network; the user unit comprises electric equipment or electric appliances, a photovoltaic power generation module, a wind power generation module and an electric automobile; the cogeneration unit takes natural gas as a raw material, outputs electric energy and supplies heat to the outside, and the heat supply and the power supply of the cogeneration unit are positioned in a feasible working interval; the boiler unit takes natural gas as a raw material and supplies heat to the outside. The invention also provides a scheduling method, the intelligent computing module selects electricity purchasing and selling strategies and gas purchasing strategies of the user unit, the power generation unit, the cogeneration unit, the boiler unit and the main power grid through an accelerated intelligent algorithm, and each unit and the main power grid carry out distributed electricity purchasing and selling transactions and heat supply transactions through a block chain system. The invention sets a price driving mechanism, promotes the consumption of new energy power generation and effectively improves the reliability of power grid operation.
Description
Technical Field
The invention belongs to the field of power grid dispatching, and particularly relates to a user demand-based intelligent power grid dispatching system and a dispatching method.
Background
In recent years, with the rapid development of new energy power generation technology, the application of the new energy power generation technology is distributed to every household. Although more and more places begin to be distributed with the distributed new energy power generation system, the new energy power generation technology has larger randomness due to the close correlation with uncertain factors such as weather, climate and the like, and further the new energy is threatened to the reliable operation of a power grid after being connected to the power grid; due to the fact that randomness is high, operation is unstable, new energy power generation is not accepted and consumed by the public, and power abandonment happens sometimes. In addition, due to the opacity of the user to the power generation condition, the user cannot reasonably arrange the power utilization time, so that the power utilization time of the load end is concentrated, and a large impact is caused on a power grid. No technical means for comprehensively solving the problems exist in the prior art. In addition, the traditional power grid adopts a centralized monitoring method, so that the reliability and the operation of the traditional power grid are not good, and the power utilization information of a user needs to be transmitted to centralized monitoring equipment, so that the problem of user privacy disclosure is easily caused.
Therefore, the technical problems that in the prior art, users use electricity in a centralized mode, privacy of the users is leaked, and the electricity generated by new energy is difficult to accept and consume by the public and the like exist.
Disclosure of Invention
The invention aims to solve the problems and provides a user demand-based intelligent power grid dispatching system, wherein a power price market allocation mechanism and a payment mechanism are completed through a block chain system, and the power consumption demand, the heat consumption demand and the power generation measuring tool of each user are measured or predicted by an intelligent instrument; the method comprises the steps of recording acquired information of the intelligent meters by means of a distributed accounting function of a block chain module or a storage function and an information interaction function of an intelligent computing module, calculating and sending the surplus of generated energy or the excess of demand of each user to a corresponding block chain metering unit of each user through each distributed intelligent computing module based on the information, and simultaneously storing generated energy and demand data of each user in a storage unit in the corresponding block chain metering unit or directly storing the data in the intelligent computing module as local information. By the method, the privacy information of each user can be better protected while the power grid is subjected to real-time power supply and power generation management. And the network topology formed by all the distributed intelligent computing modules is communicated. For users, the system carries out power scheduling according to the price of electricity and the price of gas, thereby taking scheduling action in accordance with the benefits of the power generation unit and the cogeneration unit.
The technical scheme of the invention is that the intelligent power grid dispatching system based on user requirements comprises a plurality of user units, a plurality of power generation units, a plurality of cogeneration units and a plurality of boiler units, wherein the user units, the power generation units and the cogeneration units are respectively connected with a main power grid and can introduce or transmit electric energy to the main power grid; the user unit comprises electric equipment or electric appliances, an intelligent instrument, a photovoltaic power generation module, a wind power generation module and an electric vehicle, wherein the intelligent instrument measures the generated energy of the user unit and the consumed electric quantity and heat and predicts the power consumption demand and the heat demand of a user; the cogeneration unit takes natural gas as a raw material, outputs electric energy and supplies heat to the outside, and the heat supply and the power supply of the cogeneration unit are positioned in a feasible working interval; the boiler unit takes natural gas as a raw material and supplies heat to the outside.
The intelligent power grid dispatching system based on the user demands further comprises a calculating and storing module, the calculating and storing module comprises a plurality of intelligent calculating modules, the intelligent calculating modules calculate the electric quantity purchased or sold by the user units from the main power grid in a distributed mode based on electricity price, gas price, conveying cost and a distributed network, the heat purchased from each cogeneration unit or boiler unit is formed and transmitted to corresponding units, no electric heating equipment is arranged in the user units, heating is realized in a centralized mode, the electricity purchased by the user units is only used for non-heat supply demands, the heat supply demands of the user units are met by the boiler unit heat supply or cogeneration units, the heat supply and electric quantity purchased from each cogeneration unit, the electric quantity purchased from the power generating units, the heat purchased from the boiler units, and in the day-ahead dispatching stage, through an intelligent computing module, selecting a power and gas purchasing strategy to ensure that the system runs in a working mode with maximized economic benefit; in the real-time operation process, based on the time-of-use electricity price, a service time plan of the electric appliances or the electric equipment is made for a user through the intelligent computing module, and the service time of each electric appliance or electric equipment is planned in a mode of maximizing economic benefits for the user.
A dispatching method of an intelligent power grid dispatching system based on user demands is characterized in that the sum of the number of distributed intelligent computing modules is equal to the sum of the number of user units, power generation units, cogeneration units, boiler units and a main power grid, each intelligent computing module corresponds to one user unit or power generation unit or cogeneration unit or boiler unit or main power grid, through block chain authentication, electric quantity transaction and heat supply between units or between units and the main power grid are carried out and recorded and stored through a block chain system, and purchase and sale electric quantity information and heat supply information between units or between units and the main power grid and purchase gas quantity information of the cogeneration units and the boiler units are obtained through the block chain system; the distributed network is formed by all intelligent computing modules, the network topologies corresponding to the distributed network are communicated, and the communicated intelligent computing modules are in equivalent communication; the heat demand of the user unit is supplied by the cogeneration unit and the boiler unit, and is preferentially supplied by the cogeneration unit; in the scheduling stage before the day, the intelligent computing module selects electricity purchasing, selling electricity and gas purchasing strategies of the user unit, the power generation unit, the cogeneration unit, the boiler unit and the main power grid through an accelerated intelligent algorithm, wherein the accelerated intelligent algorithm specifically comprises the following steps:
(1) the intelligent computing module respectively authenticates from the block chain system, acquires the electricity purchasing quantity information, the gas purchasing quantity information, the electricity selling quantity information to other units or the main power grid and the heat demand of the user unit, which are calculated by other intelligent computing modules, from other user units, the electricity generating unit, the cogeneration unit and the main power grid;
(2) each intelligent calculation module calculates and stores corresponding collaborative parameters based on the correspondingly acquired electricity purchasing quantity information, the correspondingly acquired gas purchasing quantity information and the correspondingly acquired electricity selling quantity information;
(3) each intelligent calculation module calculates and stores corresponding electricity purchasing information, gas purchasing information and electricity selling information based on the corresponding electricity purchasing information, gas purchasing information and electricity selling information which are obtained by the intelligent calculation module correspondingly and corresponding collaborative parameters obtained by the intelligent calculation module in the last calculation, and the current corresponding electricity price and gas price;
(4) judging whether the difference value of the electricity purchasing quantity and the air purchasing quantity calculated by the intelligent calculation module twice in the adjacent process does not exceed a set threshold value;
(4a) if the difference value between the electricity purchasing quantity and the gas purchasing quantity calculated in two adjacent times does not exceed the set threshold value, each intelligent calculation module submits the information of the electricity purchasing quantity and the gas purchasing quantity calculated by the intelligent calculation module to the block chain system, and the step (5) is executed;
(4b) if the difference value of the purchased and sold electricity or the purchased gas amount calculated in two adjacent times exceeds a set threshold value, returning to the step (1);
(5) each user unit, the power generation unit, the cogeneration unit, the boiler unit and the main power grid acquire the corresponding electricity purchasing information, gas purchasing information and electricity selling information obtained by the last calculation in a distributed manner from the block chain system, and perform power production and heat supply heat energy production based on the information;
(6) each unit carries out distributed electricity purchasing and selling transaction and heat supply transaction through the block chain system, and carries out electricity supply and heat supply.
The step (2) specifically comprises the following steps:
(2a) numbering a plurality of user units, a plurality of power generation units, a plurality of cogeneration units and a plurality of boiler units as 1,2, … N in sequence, and numbering a main power grid as N +1, wherein N is the sum of the numbers of the user units, the power generation units, the cogeneration units and the boiler units; (2b) for the unit i with the number i, i is 1,2, … N +1, when the unit is a user unit or a power generation unit or a cogeneration unit, the electric quantity coordination parameter of the corresponding intelligent calculation module i is calculated iteratively through the following formula,
wherein
The value of the obtained co-parameter, g, for the k-th calculation of unit iiIs the current power generation of cell i, diIs the current power demand of unit i,
the value of the electric quantity sold to the unit j by the unit i obtained by the k calculation,
for the electric quantity value sold from the unit j to the unit i obtained by the k-th calculation, the electric quantity cooperative parameter is selected during the first calculation
Initial value of
(2C) For the unit i, when the unit i is a cogeneration unit or a boiler unit, the corresponding intelligent calculation module i iteratively calculates the heat coordination parameter thereof by the following formula,
wherein
The heat quantity synergistic parameter obtained by the k calculation, h is the sum of the heat quantity requirements of all units,
calculating the gas purchase amount of the unit i obtained for the k iteration, wherein aiSelecting initial values of heat synergistic parameters for the energy conversion efficiency of the corresponding cogeneration unit or boiler unit at the time of first calculation
The step (3) specifically comprises the following steps,
(3a) according to the current electricity price and gas price, a performance index function c is established for representing the investment consumption of the power grid,
wherein p isijThe price of electricity sold to the unit j or the main grid for the unit i or the main grid; if either unit i or unit j is a boiler unit, then pij＝0；niGas price, s, for natural gas purchase for Unit iiThe gas purchase amount is;
(3b) for the unit i, the unit i is iteratively updated by the corresponding intelligent computing module i through the following formula
Wherein argmin { } denotes the corresponding x that minimizes the function in bracesijAnd siA, beta are constant coefficients,
for the electric quantity value sold from unit i to unit j obtained by k step calculation, selecting initial value when first calculating
And
selling price p of electricity from power generation unit to other units related to solar power generation or wind power generationijLower than the selling price p of selling electricity from the generating unit not related to solar power generation or wind power generation to other unitsji。
The invention has the beneficial effects that:
(1) by using the block chain system and the intelligent computing module for information interaction, the user unit, the power generation unit, the cogeneration unit and the boiler unit can perform information interaction pairwise, so that the discovery and the transmission to the outside are easier when a fault occurs, and the reliability of a power grid is greatly enhanced. Meanwhile, the state of the unit can be quickly transmitted to the block chain system and the corresponding intelligent computing module, and the intelligent computing module can be used for quickly diagnosing faults, so that the fault diagnosis efficiency is improved, and the reliability of the power grid is enhanced. The intelligent computing module can send instructions to the faulty units in real time through the network, and is used for removing faults to enable the power grid to recover to be normal, so that the fault maintenance process is accelerated.
(2) The scheduling method based on the intelligent computing module enables the electricity purchasing and selling information of the users and the electricity utilization schedule not to be directly transmitted among all the users, so that the privacy of the users is well protected.
(3) The scheduling method based on the intelligent computing module does not need to manually schedule the power market day by day, so that labor resources are saved;
(4) the reliability of the operation of the power grid is effectively enhanced. Because the user can be the electricity generation end, can be the power consumption end, also can be both electricity generation end and user to can realize the nimble dispatch of electric power, reduce transmission distance, electricity generation and power consumption efficiency obtain promoting. The utilization efficiency of energy can be improved through the electrical allocation of the power system.
(5) A price driving and exciting mechanism is set, and consumption of new energy power generation is promoted.
(6) Through the intelligent computing module, on the premise of protecting data privacy of a user and a power generation end, electricity and gas purchasing strategies can be selected, and a service time plan of an electric appliance is made for the user, so that the cost and carbon dioxide emission of the power generation end are reduced, the user can participate in scheduling by reasonably arranging the service time of the electric appliance, and the technical effect of reducing the impact on a power grid is further achieved; meanwhile, the combination of the two technical means can also reasonably reduce the electricity utilization cost of users. The intelligent calculation module selects electricity and gas purchasing strategies for the power generation end and the heat supply end, and the service time plan of the electric appliance is made for the user, so that the technical effects of bringing economic benefits to the power generation end, the heat supply end and the user and further enhancing the reliability of the power grid can be achieved.
(7) By adopting the intelligent acceleration algorithm provided by the invention to select the electricity and gas purchasing strategies, the reliability of the whole decision making process can be ensured. Although the electric loads at the load end are time-varying in the real-time power dispatching process, as long as the variation rate of the electric loads is lower than the calculation convergence rate of the intelligent acceleration algorithm provided by the invention, the intelligent acceleration algorithm can process the time-varying loads in real time, so that the reliability of the power dispatching process is ensured.
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The invention is further illustrated by the following figures and examples.
Fig. 1 is a schematic diagram of the physical connection of the present invention.
FIG. 2 is a diagram of information connection according to the present invention.
Fig. 3 is a flowchart illustrating a scheduling method according to the present invention.
Detailed Description
Example one
As shown in fig. 1 and fig. 2, a smart grid dispatching system based on user demand includes: the system comprises a plurality of user units taking families as units, a plurality of power generation units, a plurality of cogeneration units and a plurality of boiler modules; the user unit, the power generation unit and the cogeneration unit are respectively connected with the main grid and can introduce or deliver electric energy to the main grid. The household consumer unit comprises household appliances such as a refrigerator, a washing machine, a dish washing machine, an electric lamp and a television, and also comprises an intelligent instrument, a photovoltaic power generation module, a wind power generation module and an electric automobile, wherein the intelligent instrument measures the generated energy of the consumer unit and the consumed electric quantity and heat and predicts the electricity consumption demand and heat demand of a user; the cogeneration unit takes natural gas as a raw material and can output electric energy and supply heat to the outside, and the heat supply and the power supply of the cogeneration unit are positioned in a feasible working interval; the boiler unit takes natural gas as a raw material and supplies heat to the outside.
The intelligent power grid dispatching system based on the user demands further comprises a calculating and storing module, the calculating and storing module comprises a plurality of distributed calculating modules, the distributed calculating modules are used for calculating the electric quantity purchased or sold from the regional power grid by each user unit taking a family as a unit in a distributed mode based on the electricity price, the gas price, the conveying cost and the distributed network, the heat supply quantity purchased from each cogeneration unit or boiler unit is formed, and an electricity purchasing/transmitting instruction and a heat supply instruction are formed and transmitted to the corresponding family user units. The household user units are not provided with heating equipment and adopt a centralized mode for heating, wherein the purchased electricity is only used for non-heating requirements in a household, the heating requirements are met by a boiler heating or cogeneration system, the heat supply and the electricity purchased from each cogeneration unit are purchased from the boiler unit, and in the day-ahead scheduling stage, the electricity purchasing and gas purchasing strategies are selected through a distributed computing module to ensure that the system runs in a working mode with maximized economic benefits; in the real-time operation process, on the basis of the time-of-use electricity price, a service time plan of the electric appliances is made for a user through the distributed computing module, and the service time of each electric appliance is planned in a mode of ensuring that the user maximizes economic benefits. Through the scheme, the energy supply and demand balance of the whole power grid is met. The optimal instruction is obtained through distributed operation by combining the energy excess and shortage of each user, and the optimal instruction is sent out to control the power generation and power transmission of each user.
The system comprises a plurality of power generation and utilization modules, a plurality of power generation modules and a plurality of cogeneration units, wherein the power generation and utilization modules take families as units. The user unit taking a family as a unit comprises household appliances such as a refrigerator, a washing machine, a dish washing machine and the like and renewable energy power generation modules such as a photovoltaic power generation module and a wind power generation module. The cogeneration unit takes natural gas as a raw material and can output electric energy to the outside and supply heat and cold to the outside, the heat supply, cold supply and power supply of the cogeneration unit are positioned in a feasible working interval, the electricity generation waste heat and the waste heat generated by cold supply both participate in the transaction of a block chain, and electricity-air conditioning is carried out through the block chain, so that the multi-scale calling of energy is promoted. When the electric power is scheduled, when the electric quantity is insufficient, the electric power is scheduled according to the following priority: the power utilization requirements of strategic users are met firstly, and then the power utilization requirements of other users are met.
Preferably, the user unit is equipped with a heat engine, a photovoltaic, a wind power generation, an electric automobile, an elastic load, and the like.
Preferably, the distributed computing module further comprises a carbon dioxide certification link, the optimization target comprises a carbon dioxide emission index, and by minimizing the total economic index, not only can cost control be optimized, but also the use of clean energy can be promoted.
As shown in fig. 3, in the scheduling method of the smart grid scheduling system based on user requirements adopted in this embodiment, the number of distributed computing modules is equal to the sum of the numbers of the user units, the power generation units, the cogeneration units, the boiler units and the main grid, each intelligent computing module corresponds to one user unit or one power generation unit or one cogeneration unit or one boiler unit or one main grid, and acquires information of purchased electric quantity, purchased air quantity information and information of sold electric quantity to other user units and the main grid from the corresponding user units, power generation units and cogeneration units through block chain authentication; the distributed computing modules form a distributed network, network topologies corresponding to the distributed network are communicated, and the communicated distributed computing modules are communicated equivalently.
In the day-ahead scheduling stage, the distributed computing module selects electricity purchasing and gas purchasing strategies of each user unit, each power generation unit and each cogeneration unit through an accelerated intelligent algorithm, and the accelerated intelligent algorithm specifically comprises the following steps:
(1) the distributed calculation module acquires the electricity purchasing information, the gas purchasing information, the selling information of the electricity sold to other user units and the main power grid and the heat demand of each user from other user units, the electricity generation unit, the combined heat and power generation unit and the main power grid which are obtained by the last step of calculation from the corresponding user units, the electricity generation unit and the combined heat and power generation unit respectively through block chain authentication;
(2) and each distributed calculation module calculates and stores corresponding collaborative parameters based on the correspondingly acquired electricity purchasing quantity information, the correspondingly acquired gas purchasing quantity information and the correspondingly acquired electricity selling quantity information. For each user, when the generated energy is larger than the electricity demand of the user, the value of the cooperative parameter is increased to represent that the cooperative parameter can output electric energy outwards; when the generated energy is smaller than the demand of the user, the value of the cooperative parameter is reduced, and the cooperative parameter represents that the cooperative parameter can absorb the electric energy;
(3) each distributed calculation module calculates and stores corresponding electricity purchasing information, gas purchasing information and electricity selling information by utilizing an accelerated intelligent algorithm based on the correspondingly obtained electricity purchasing information, gas purchasing information and electricity selling information and corresponding collaborative parameters obtained by the previous calculation and the current corresponding electricity price;
(4) repeating the steps (1) to (3) until the difference value between the purchased gas amount information and the sold electricity amount information does not exceed a set threshold value after the purchased electricity amount information and the sold electricity amount information are calculated for two adjacent times;
(5) each user unit, the power generation unit and the cogeneration unit acquire the corresponding electricity purchasing information, gas purchasing information and electricity selling information obtained by the last calculation from the block chain system in a distributed manner, and perform power production and heat supply heat energy production based on the information;
(6) each unit carries out distributed electricity purchasing and selling transaction and heat supply transaction through the block chain system, and carries out electricity supply and heat supply. It is preferred.
Preferably, step (2) comprises the following sub-steps:
(2a) numbering a user unit, a power generation unit and a cogeneration unit as 1,2,. N in sequence, and numbering a main power grid as N +1, wherein N is the sum of the numbers of the user unit, the power generation unit, the cogeneration unit and a boiler unit;
(2b) for the unit i, when the unit i is a user unit or a power generation unit or a cogeneration unit, the corresponding distributed computation module i iteratively computes the electric quantity coordination parameter of the unit i through the following formula,
wherein
The value of the obtained co-parameter, g, for the k-th calculation of unit iiIs the current power generation of cell i, diIs the current power demand of unit i,
the value of the electric quantity sold to the unit j by the unit i obtained by the k calculation,
for the electric quantity value sold from the unit j to the unit i obtained by the k-th calculation, the electric quantity cooperative parameter is selected during the first calculation
Initial value of
(2c) For the unit i, when the unit i is a cogeneration unit or a boiler unit, the corresponding distributed computing module i iteratively computes the heat coordination parameter of the unit i through the following formula,
wherein
The heat quantity synergistic parameter obtained by the k calculation, h is the sum of the heat quantity requirements of all units,
calculating the gas purchase amount of the unit i obtained for the k iteration, wherein aiSelecting initial values of heat synergistic parameters for the energy conversion efficiency of the corresponding cogeneration unit or boiler unit at the time of first calculation
Preferably, step (3) comprises the following sub-steps,
(3a) according to the current electricity price and the gas price, a performance index function c is established, and the investment consumption for representing the power grid is as follows:
wherein p isijThe unit with the number i or the main grid sells electricity to the unit with the number j or the main grid; if the unit numbered i or the unit numbered j corresponds to a boiler module, pij＝0；niGas price, s, for the unit numbered iiTo purchaseGas quantity; (3b) for the unit i, the unit i is iteratively updated by the corresponding intelligent computing module i through the following formula
Wherein argmin { } denotes the corresponding x that minimizes the function in bracesijAnd siA, beta are constant coefficients,
for the electric quantity value sold from unit i to unit j obtained by k step calculation, selecting initial value when first calculating
And
preferably, the electricity selling price p of electricity sold by the power generation unit to other units when the solar power generation unit or the wind power generation unit is involvedijSelling price p of electricity to other units lower than electricity generation of unit not related to solar power generation unit or wind power generation unitji。
Preferably, the synergy parameter
Initial value, synergistic parameter
Initial value,
Initial value sum
The initial value is optional.
Preferably, when none of the units is connectable to, cannot introduce or deliver electrical energy to, or to, the main grid, step (2a) is replaced by:
(2a1) numbering a user unit, a power generation unit, a cogeneration unit and a boiler unit as 1, 2.. N in sequence, wherein N is the sum of the number of the user unit, the power generation unit, the cogeneration unit and the boiler unit;
replacing step (3a) with:
(3a1) according to the current electricity price and the current gas price, a performance index function c is established, and the investment consumption for representing the power grid is as follows:
wherein p isijThe unit with the number i or the main grid sells electricity to the unit with the number j or the main grid; if the unit numbered i or the unit numbered j corresponds to a boiler module, pij＝0；niGas price, s, for the unit numbered iiThe gas purchase amount is; in general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
(1) by using the blockchain system for information interaction, users are equivalent to energy subnets, and information interaction can be performed among the users, so that the users can find and transmit the information to the outside more easily when a fault occurs, and the reliability of a power grid is greatly enhanced. Meanwhile, the state of the user can be quickly transmitted to the block chain system, and the module can be used for quickly diagnosing faults, so that the fault diagnosis efficiency is accelerated, and the reliability of the power grid is enhanced. The block chain system or the distributed computing module can send instructions to the users with faults in real time through the network, and the instructions are used for removing the faults to enable the power grid to be recovered to be normal, so that the fault maintenance process is accelerated.
(2) By the scheduling method based on the block chain system and the distributed computing module, the power generation information and the power utilization schedule of the family users do not need to be directly transmitted among all the users, so that the privacy of the users is well protected.
(3) By the scheduling method based on the block chain system and the distributed computing module, the day-ahead scheduling of the power market is not needed manually, and labor resources are saved;
(4) the reliability of the operation of the power grid is effectively enhanced. Because the user can be the electricity generation end, can be the power consumption end, also can be both the electricity generation end and the user side, for example possess renewable energy power generation system's the home unit to can realize the nimble dispatch of electric power, reduce transmission distance, electricity generation and power consumption efficiency obtain promoting. The utilization efficiency of energy can be improved through the electrical allocation of the power system.
(5) A price driving mechanism is set, and consumption of new energy power generation is promoted.
(6) Through the block chain system and the distributed computing module, the electricity and gas purchasing strategy can be selected on the premise of protecting the data privacy of the user and the power generation end, and the service time plan of the electric appliance is made for the user, so that the cost and the carbon dioxide emission of the power generation end are reduced, the user can participate in scheduling by reasonably arranging the service time of the electric appliance, and the technical effect of reducing the impact on a power grid is further achieved; meanwhile, the combination of the two technical means can also reasonably reduce the electricity utilization cost of users. Namely, the block chain system and the distributed computing module are used for selecting electricity and gas purchasing strategies for the power generation end and the heat supply end, and the service time plan of the electric appliance is made for the user, so that the technical effects of bringing economic benefits to the power generation end, the heat supply end and the user and further enhancing the reliability of the power grid can be achieved.
(7) The adoption of the intelligent acceleration algorithm provided by the invention to select the electricity and gas purchasing strategy can ensure the reliability of the whole decision process. Although the electric load at the load end is time-varying in the real-time power dispatching process, as long as the variation rate of the electric load is lower than the calculation convergence rate of the intelligent acceleration algorithm provided by the invention, the intelligent acceleration algorithm can be used for processing the time-varying loads, so that the reliability of the power dispatching process is ensured.
Example two
As shown in fig. 1 and fig. 2, the smart grid dispatching system based on user requirements in this embodiment includes: the household power generation system comprises a plurality of user units taking families as units, a plurality of power generation units, a plurality of cogeneration units and a plurality of boiler units, wherein the user units, the power generation units, the cogeneration units and the boiler units are respectively connected with a main power grid and can introduce or transmit electric energy to the main power grid. The household electric appliance comprises household electric appliances such as a refrigerator, a washing machine, a dish washing machine, an electric lamp and a television, and also comprises an intelligent instrument, a photovoltaic power generation module, a wind power generation module and an electric automobile, wherein the intelligent instrument measures the generated energy of a user unit and the consumed electric quantity and heat and predicts the electricity consumption demand and heat demand of the user; the cogeneration unit takes natural gas as a raw material and can output electric energy and supply heat to the outside, and the heat supply and the power supply of the cogeneration unit are positioned in a feasible working interval; the boiler unit takes natural gas as a raw material and supplies heat to the outside.
The intelligent power grid dispatching system based on the user demands further comprises a calculating and storing module, the calculating and storing module comprises a plurality of intelligent calculating modules, the intelligent calculating modules are used for calculating the electric quantity purchased or sold from the regional power grid by each power generation and utilization unit taking a family as a unit in a distributed mode based on the electricity price, the gas price, the conveying cost and the wireless communication network, the heat supply quantity purchased from each cogeneration unit or boiler unit is formed, and an electricity purchasing/power transmission instruction and a heat supply instruction are formed and transmitted to the corresponding family user units. The household user unit is provided with no heating equipment and adopts a centralized heating mode to supply heat, wherein the purchased electricity is only used for non-heat supply requirements in a household, the heat supply requirements are met by a boiler heat supply or combined heat and power generation system, the heat supply quantity and the electric quantity purchased from each combined heat and power generation module are purchased from the boiler unit, and in the day-ahead scheduling stage, the electricity purchasing and gas purchasing strategies are selected through an intelligent computing module to ensure that the system runs in a working mode with maximized economic benefits; in the real-time operation process, on the basis of the time-of-use electricity price, the service time plan of the electric appliances is made for the user through the intelligent computing module, and the service time of each electric appliance is planned in a mode of maximizing economic benefits for the user.
Through the scheme, the energy supply and demand balance of the whole power grid is met. The optimal instruction is obtained through distributed operation by combining the energy excess and shortage of each user, and the optimal instruction is sent out to control the power generation and power transmission of each user.
When the electric power is scheduled, when the electric quantity is insufficient, the electric power is scheduled according to the following priority: the power utilization requirements of strategic users are met firstly, and then the power utilization requirements of other users are met.
Preferably, a heat engine, a photovoltaic, a wind power generation, an electric vehicle, an elastic load, and the like are equipped in a home.
Preferably, the intelligent computing module further comprises a carbon dioxide authentication link, the optimization target comprises a carbon dioxide emission index, and by minimizing the total economic index, not only can cost control be optimized, but also the use of clean energy can be promoted.
As shown in fig. 3, in the scheduling method of the smart grid scheduling system based on user requirements in this embodiment, the number of the smart computing modules is equal to the sum of the numbers of the user units, the power generation units, the cogeneration units, and the main grid, each smart computing module corresponds to one user unit or one power generation unit or one cogeneration unit or one boiler unit or one main grid, and each smart computing module is in wireless communication, that is, information can be transmitted between any two smart computing modules through wireless communication. In the day-ahead scheduling stage, the intelligent calculation module selects each user unit, each power generation unit and the electricity and gas purchasing strategies of each cogeneration unit through an accelerated intelligent algorithm, and the accelerated intelligent algorithm specifically comprises the following steps:
(1) the plurality of calculation modules respectively acquire the electric quantity purchasing information, the gas purchasing information, the selling information of the electric quantity sold to other user units and the main power grid and the heat demand of each user unit from other user units, the power generation unit, the cogeneration unit and the main power grid which are obtained by the previous step through calculation from the corresponding user units, the power generation unit and the cogeneration unit through a communication network;
(2) each intelligent calculation module calculates and stores corresponding collaborative parameters based on the correspondingly acquired electricity purchasing quantity information, the correspondingly acquired gas purchasing quantity information and the correspondingly acquired electricity selling quantity information;
(3) each intelligent calculation module calculates and stores corresponding electricity purchasing amount information, corresponding gas purchasing amount information and corresponding electricity selling amount information based on the corresponding electricity purchasing amount information, corresponding gas purchasing amount information and corresponding electricity selling amount information which are obtained by the corresponding intelligent calculation module and corresponding collaborative parameters obtained by the previous calculation;
(4) repeating the steps (1) to (3) until the difference value between the purchased gas amount information and the sold electricity amount information does not exceed a set threshold value after the purchased electricity amount information and the sold electricity amount information are calculated for two adjacent times;
(5) each user unit, the power generation unit, the cogeneration unit and the boiler unit acquire the corresponding electricity purchasing information, gas purchasing information and electricity selling information obtained by the last calculation in a distributed manner from the intelligent calculation module, and perform power production and heat supply energy production based on the information;
(6) each user unit, the power generation unit, the cogeneration unit and the boiler unit supply electricity and heat.
Preferably, step (2) comprises the following sub-steps:
(2a) numbering a user unit, a power generation unit and a cogeneration unit as 1,2,. N in sequence; numbering a main power grid as N + 1; wherein N is the sum of the number of the user units, the power generation units, the cogeneration units and the boiler units;
(2b) for the unit i, when the unit i is a user unit or a power generation unit or a cogeneration unit, the corresponding distributed computation module i iteratively computes the electric quantity coordination parameter of the unit i through the following formula,
wherein
The value of the obtained co-parameter, g, for the k-th calculation of unit iiIs the current power generation of cell i, diIs the current power demand of unit i,
the value of the electric quantity sold to the unit j by the unit i obtained by the k calculation,
for the electric quantity value sold from the unit j to the unit i obtained by the k-th calculation, the electric quantity cooperative parameter is selected during the first calculation
Initial value of
(2c) For the unit i, when the unit i is a cogeneration unit or a boiler unit, the corresponding distributed computing module i iteratively computes the heat coordination parameter of the unit i through the following formula,
wherein
The heat quantity synergistic parameter obtained by the k calculation, h is the sum of the heat quantity requirements of all units,
calculating the gas purchase amount of the unit i obtained for the k iteration, wherein aiSelecting initial values of heat synergistic parameters for the energy conversion efficiency of the corresponding cogeneration unit or boiler unit at the time of first calculation
Preferably, step (3) comprises the following sub-steps:
(3a) according to the current electricity price and the gas price, a performance index function c is established, and the investment consumption for representing the power grid is as follows:
wherein p isijThe unit with the number i or the main grid sells electricity to the unit with the number j or the main grid; if the unit numbered i or the unit numbered j corresponds to a boiler module, pij＝0；niGas price, s, for the unit numbered iiThe gas purchase amount is; (3b) for the unit i, the unit i is iteratively updated by the corresponding intelligent computing module i through the following formula
Wherein argmin { } denotes the corresponding x that minimizes the function in bracesijAnd siA, beta are constant coefficients,
for the electric quantity value sold from unit i to unit j obtained by k step calculation, selecting initial value when first calculating
And
preferably, the electricity selling price p of the electricity selling from the electricity generating unit related to the solar power generation or the wind power generation to other unitsijLower than the selling price p of selling electricity from the generating unit not related to solar power generation or wind power generation to other unitsji。
Preferably, the electric quantity is a parameter
Initial value and heat quantity cooperative parameter
Initial value,
Initial value sum
The initial value is optional.
Preferably, when none of the units is connectable to, cannot draw in or deliver electrical energy from or to the main grid, step (2a) is replaced by:
(2a1) numbering a user unit, a power generation unit and a thermoelectricity cogeneration module as 1,2,. N in sequence, wherein N is the sum of the number of the user unit, the power generation unit, the thermoelectricity cogeneration unit and a boiler unit;
replacing step (3a) with:
(3a1) according to the current electricity price and the gas price, a performance index function c is established, and the investment consumption for representing the power grid is as follows:
wherein p isijThe unit with the number i or the main grid sells electricity to the unit with the number j or the main grid; if the unit numbered i or the unit numbered j corresponds to a boiler module, pij＝0；niGas price, s, for the unit numbered iiThe gas purchase amount is; in general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
(1) through information interaction among users, when a fault occurs, the fault is found and transmitted to the outside more easily, and therefore the reliability of the power grid is greatly enhanced. Meanwhile, the state of the user can be quickly transmitted to the intelligent computing module, and the fault diagnosis can be carried out more quickly by using the module, so that the fault diagnosis efficiency is accelerated, and the reliability of the power grid is enhanced.
(2) By the scheduling method, the day-ahead scheduling of the power market is not needed manually, and labor resources are saved.
(3) The reliability of the operation of the power grid is effectively enhanced. Because the user can be the electricity generation end, can be the power consumption end, also can be both the electricity generation end and the user side, for example possess the family of renewable energy power generation system to can realize the nimble dispatch of electric power, reduce transmission distance, electricity generation and power consumption efficiency obtain promoting. The utilization efficiency of energy can be improved through the electrical allocation of the power system.
(4) A price driving mechanism is set, and consumption of new energy power generation is promoted.
(5) Through the intelligent computing module, electricity and gas purchasing strategies can be selected, and a service time plan of the electric appliance is made for a user, so that the cost of a power generation end and the emission of carbon dioxide are reduced, the user can participate in scheduling by reasonably arranging the service time of the electric appliance, and the technical effect of reducing the impact on a power grid is further achieved; meanwhile, the combination of the two technical means can also reasonably reduce the electricity utilization cost of users. The intelligent calculation module selects electricity and gas purchasing strategies for the power generation end and the heat supply end, the service time plan of the electric appliance is made for the user, economic benefits can be brought to the power generation end, the heat supply end and the user, and the technical effect of further enhancing the reliability of the power grid can be achieved.
(6) The adoption of the intelligent acceleration algorithm provided by the invention to select the electricity and gas purchasing strategy can ensure the reliability of the whole decision process. Although the electric load at the load end is time-varying in the real-time power dispatching process, as long as the variation rate of the electric load is lower than the calculation convergence rate of the intelligent acceleration algorithm provided by the invention, the intelligent acceleration algorithm can be used for processing the time-varying loads, so that the reliability of the power dispatching process is ensured.
Claims (3)
1. The intelligent power grid dispatching system based on the user demands is characterized by comprising a plurality of user units, a plurality of power generation units, a plurality of cogeneration units and a plurality of boiler units, wherein the user units, the power generation units and the cogeneration units are respectively connected with a main power grid and can introduce or transmit electric energy to the main power grid; the user unit comprises electric equipment or electric appliances, a photovoltaic power generation module, a wind power generation module and an electric automobile; the cogeneration unit takes natural gas as a raw material, outputs electric energy and supplies heat to the outside, and the heat supply and the power supply of the cogeneration unit are positioned in a feasible working interval; the boiler unit takes natural gas as a raw material and supplies heat to the outside;
the intelligent power grid dispatching system based on the user demands further comprises a calculating and storing module, the calculating and storing module comprises a plurality of intelligent calculating modules, the intelligent calculating modules calculate the electric quantity purchased or sold by the user units from the main power grid in a distributed mode based on electricity price, gas price, conveying cost and a distributed network, the heat purchased from each cogeneration unit or boiler unit is formed and transmitted to corresponding units, no electric heating equipment is arranged in the user units, heating is realized in a centralized mode, the electricity purchased by the user units is only used for non-heat supply demands, the heat supply demands of the user units are met by the boiler unit heat supply or cogeneration units, the heat supply and electric quantity purchased from each cogeneration unit, the electric quantity purchased from the power generating units, the heat purchased from the boiler units, and in the day-ahead dispatching stage, through an intelligent computing module, selecting a power and gas purchasing strategy to ensure that the system runs in a working mode with maximized economic benefit; in the real-time operation process, based on the time-of-use electricity price, a service time plan of the electric appliances or the electric equipment is made for a user through an intelligent computing module, and the service time of each electric appliance or electric equipment is planned in a mode of maximizing economic benefits for the user;
the number of the distributed intelligent computing modules is equal to the sum of the numbers of the user units, the power generation units, the cogeneration units, the boiler units and the main power grid, each intelligent computing module corresponds to one user unit or one power generation unit or one cogeneration unit or one boiler unit or one main power grid, electric quantity transaction and heat supply between the units or between the units and the main power grid are recorded and stored through a block chain system through block chain authentication, and purchase and sale electric quantity information and heat supply information between the units or between the units and the main power grid and purchase gas quantity information of the cogeneration units and the boiler units are obtained through the block chain system; the distributed network is formed by all intelligent computing modules, the network topologies corresponding to the distributed network are communicated, and the communicated intelligent computing modules are in equivalent communication; the heat demand of the user unit is supplied by the cogeneration unit and the boiler unit, and is preferentially supplied by the cogeneration unit;
in the scheduling stage before the day, the intelligent computing module selects electricity purchasing, selling electricity and gas purchasing strategies of the user unit, the power generation unit, the cogeneration unit, the boiler unit and the main power grid through an accelerated intelligent algorithm, wherein the accelerated intelligent algorithm specifically comprises the following steps:
(1) the intelligent computing module respectively authenticates from the block chain system, acquires the electricity purchasing quantity information, the gas purchasing quantity information, the electricity selling quantity information to other units or the main power grid and the heat demand of the user unit, which are calculated by other intelligent computing modules, from other user units, the electricity generating unit, the cogeneration unit and the main power grid;
(2) each intelligent calculation module calculates and stores corresponding collaborative parameters based on the correspondingly acquired electricity purchasing quantity information, the correspondingly acquired gas purchasing quantity information and the correspondingly acquired electricity selling quantity information;
(3) each intelligent calculation module calculates and stores corresponding electricity purchasing information, gas purchasing information and electricity selling information based on the corresponding electricity purchasing information, gas purchasing information and electricity selling information which are obtained by the intelligent calculation module and corresponding collaborative parameters obtained by the intelligent calculation module in the last calculation, the current corresponding electricity price and gas price,
(4) judging whether the difference value of the electricity purchasing quantity and the air purchasing quantity calculated by the intelligent calculation module twice in the adjacent process does not exceed a set threshold value;
(4a) if the difference value between the electricity purchasing quantity and the gas purchasing quantity calculated in two adjacent times does not exceed the set threshold value, each intelligent calculation module submits the information of the electricity purchasing quantity and the gas purchasing quantity calculated by the intelligent calculation module to the block chain system, and the step (5) is executed;
(4b) if the difference value of the purchased and sold electricity or the purchased gas amount calculated in two adjacent times exceeds a set threshold value, returning to the step (1);
(5) each user unit, the power generation unit, the cogeneration unit, the boiler unit and the main power grid acquire the corresponding electricity purchasing information, gas purchasing information and electricity selling information obtained by the last calculation in a distributed manner from the block chain system, and perform power production and heat supply heat energy production based on the information;
(6) each user unit, the power generation unit, the cogeneration unit, the boiler unit and the main power grid carry out distributed electricity purchasing and selling transactions and heat supply transactions through a block chain system, and carry out electricity supply and heat supply;
the step (2) specifically comprises the following steps:
(2a) numbering a plurality of user units, a plurality of power generation units, a plurality of cogeneration units and a plurality of boiler units as 1,2, … N in sequence, and numbering a main power grid as N +1, wherein N is the sum of the numbers of the user units, the power generation units, the cogeneration units and the boiler units; (2b) for the unit i with the number i, i is 1,2, … N +1, when the unit is a user unit or a power generation unit or a cogeneration unit, the electric quantity coordination parameter of the corresponding intelligent calculation module i is calculated iteratively through the following formula,
wherein
The value of the obtained co-parameter, g, for the k-th calculation of unit iiIs the current power generation of cell i, diIs the current power demand of unit i,
the value of the electric quantity sold to the unit j by the unit i obtained by the k calculation,
for the electric quantity value sold from the unit j to the unit i obtained by the k-th calculation, the electric quantity cooperative parameter is selected during the first calculation
Initial value of
(2C) For the unit i, when the unit i is a cogeneration unit or a boiler unit, the corresponding intelligent calculation module i iteratively calculates the heat coordination parameter thereof by the following formula,
wherein
The heat quantity synergistic parameter obtained by the k calculation, h is the sum of the heat quantity requirements of all units,
calculating the gas purchase amount of the unit i obtained for the k iteration, wherein aiSelecting initial values of heat synergistic parameters for the energy conversion efficiency of the corresponding cogeneration unit or boiler unit at the time of first calculation
2. The smart grid dispatching system of claim 1, wherein the step (3) comprises the steps of,
(3a) according to the current electricity price and gas price, a performance index function c is established for representing the investment consumption of the power grid,
wherein p isijThe price of electricity sold to the unit j or the main grid for the unit i or the main grid; if either unit i or unit j is a boiler unit, then pij＝0；niGas price, s, for natural gas purchase for Unit iiThe gas purchase amount is;
(3b) for the unit i, the unit i is iteratively updated by the corresponding intelligent computing module i through the following formula
Wherein argmin { } denotes the corresponding x that minimizes the function in bracesijAnd siA, beta are constant coefficients,
for the electric quantity value sold from unit i to unit j obtained by k step calculation, selecting initial value when first calculating
And
3. the smart grid dispatching system of claim 2, wherein the electricity selling price p of the electricity selling from the electricity generating unit related to solar power generation or wind power generation to other unitsijLower than the selling price p of selling electricity from the generating unit not related to solar power generation or wind power generation to other unitsji。
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
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| EP3039771B1 (en) * | 2013-08-28 | 2018-05-09 | Robert Bosch GmbH | System and method for energy asset sizing and optimal dispatch |
-
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
|---|
| 含分布式电源和可调负荷的售电公司优化调度模型;顾伟 等;《电力系统自动化》;20170725;第41卷(第14期);37-44 * |
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