CN110797904B - Micro-grid ordered power utilization scheduling method and device based on typical load - Google Patents
Micro-grid ordered power utilization scheduling method and device based on typical load Download PDFInfo
- Publication number
- CN110797904B CN110797904B CN201810860460.XA CN201810860460A CN110797904B CN 110797904 B CN110797904 B CN 110797904B CN 201810860460 A CN201810860460 A CN 201810860460A CN 110797904 B CN110797904 B CN 110797904B
- Authority
- CN
- China
- Prior art keywords
- load
- power
- microgrid
- electricity
- typical
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Landscapes
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a micro-grid ordered power utilization scheduling method and device based on a typical load, wherein the method comprises the following steps: obtaining the classification of typical loads, establishing a mathematical model according to the type of each load of the microgrid and the current electricity price, and obtaining an optimization objective function and constraint conditions; according to the game theory viewpoint, the optimal scheduling model is solved until the final result converges to Nash balance, and the optimal power load value of each individual unit time is obtained, so that the ordered power utilization scheduling model of the micro-grid based on the typical load is obtained; the micro-grid side automatically transfers the power load in the peak period to the off-peak period for operation through the micro-grid ordered power utilization scheduling model. The method adopts a typical load classification technology to model most of the micro-grid, and considers the constraint conditions and the running state in real life according to different characteristics, thereby effectively improving the applicability and the practicability of dispatching, realizing peak clipping, valley filling and orderly power utilization, and being simple and easy to realize.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to a microgrid ordered power utilization scheduling method and device based on typical loads.
Background
Over the past decades, power systems have evolved into large interconnected network systems that generate electricity centrally, transmitting electricity over long distances. However, with the continuous increase of the scale of the power grid, the power system has many disadvantages: the cost is high, the operation difficulty is big, and the energy structure that gives priority to thermal power has brought huge pressure for the environmental protection. With the increasing of the power load, the degree of dependence of the receiving-end power grid on external power is continuously improved, and the power system is gradually difficult to adapt to the reliability requirement and the power supply requirement of users. The concept of a microgrid is presented in the early century for this series of problems. The definition of the micro-grid in China is as follows: the micro-grid is a small power generation and distribution system formed by collecting a distributed power supply, an energy storage device, an energy conversion device and related load, monitoring and protection devices, and is an autonomous system capable of realizing self-control, protection and management. The system can be operated with a power distribution network (grid-connected operation) or can be disconnected from the power distribution network to operate independently (island operation).
In recent years, as the economy of China continues to develop, the electricity consumption is increasing day by day, and the electricity supply is relatively lagged, so that the situation of electricity shortage often occurs. The management mode of orderly power utilization in the current power market is mainly demand-side management. However, the demand side management strategy is basically a series of administrative means such as power limiting and switching off, so that the efficiency is low, the user participation is low, the user is prone to be strongly unsatisfied in the peak power utilization period, and the management mode has many defects, so that the demand side management needs to be upgraded into demand response. In all types of demand response mechanisms, the real-time electricity price updating period is short, and the real-time electricity price can continuously fluctuate every moment, so that the real-time electricity price can well reflect the power supply and demand relationship, is one of the most ideal electricity price mechanisms in the power market, can realize real-time interactive communication between a user side and a supply side, and automatically responds to the load and price change of the supply side.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, the invention aims to provide a microgrid orderly power utilization scheduling method based on typical loads, which effectively improves the applicability and the practicability of scheduling, can realize peak clipping, valley filling and orderly power utilization, and is simple and easy to realize.
The invention also aims to provide a microgrid orderly power utilization scheduling device based on the typical load.
In order to achieve the above object, an embodiment of the invention provides a microgrid ordered power utilization scheduling method based on a typical load, which includes the following steps: obtaining the classification of typical loads, establishing a mathematical model according to the type of each load of the microgrid and the current electricity price, and obtaining an optimization objective function and constraint conditions; according to the game theory viewpoint, the optimal scheduling model is solved until the final result converges to Nash balance, and the optimal power load value of each individual unit time is obtained, so that the ordered power utilization scheduling model of the micro-grid based on the typical load is obtained; and the micro-grid side automatically transfers the power load in the peak period to the off-peak period for operation through the micro-grid ordered power utilization scheduling model.
According to the microgrid ordered power utilization scheduling method based on the typical load, the microgrid formed by adding the distributed power supply and the energy storage device at the user side is considered, the typical load classification technology is adopted, most of the microgrid is modeled, the constraint conditions and the running state in real life are considered according to different characteristics of the microgrid, and the problem of a load scheduling strategy between the microgrid and a main power grid which contain the distributed power supply, the energy storage device, the energy conversion device and the typical load in a region is solved, so that the applicability and the practicability of scheduling are effectively improved, peak clipping and valley filling and ordered power utilization can be realized, and the method is simple and easy to realize.
In addition, the ordered power utilization scheduling method for the microgrid based on the typical load according to the embodiment of the invention may further have the following additional technical features:
further, in an embodiment of the present invention, the building a mathematical model according to the type of each load of the microgrid and the current power rate, and obtaining an optimization objective function and a constraint condition further includes: initializing supply-demand ratio and real-time electricity price; obtaining an updated power demand through solving an optimal strategy and optimal load scheduling according to the current real-time electricity price through the micro-grid, and issuing the updated power demand to the main power grid side; and calculating a new supply-demand ratio through the main power grid side according to the latest unit load demand of the micro power grid side, and updating and distributing real-time electricity prices according to the gear of the new supply-demand ratio.
Further, in an embodiment of the present invention, the solving the optimal scheduling model according to the game theory until the final result converges to Nash balance further includes: and when the real-time electricity price of the main power grid side and the electricity demand of the micro-grid side are not changed, the Nash balance is achieved, and the optimal ordered electricity utilization scheduling model is obtained.
Further, in an embodiment of the present invention, the typical loads are classified into an energy storage type load, an adjustable type load, a controllable type load and a base load.
Further, in one embodiment of the present invention, the microgrid comprises a total load of household electricity, industrial electricity, commercial electricity and photovoltaic and wind power generation.
In order to achieve the above object, an embodiment of another aspect of the present invention provides a microgrid orderly power utilization scheduling apparatus based on a typical load, including: the acquisition module is used for acquiring the classification of typical loads, establishing a mathematical model according to the type of each load of the microgrid and the current electricity price, and acquiring an optimization objective function and constraint conditions; the solving module is used for obtaining the optimal power utilization load value of each individual unit time by solving the optimal scheduling model according to the game theory viewpoint until the final result converges to Nash balance, so as to obtain the micro-grid ordered power utilization scheduling model based on the typical load; and the transfer module is used for automatically transferring the power load of the peak time period to the off-peak time period for operation by the micro-grid side through the micro-grid ordered power utilization scheduling model.
According to the typical load-based micro-grid ordered power utilization scheduling device, the micro-grid formed by adding the distributed power supply and the energy storage device at the user side is considered, the typical load classification technology is adopted, most parts of the micro-grid are modeled, the constraint conditions and the running state in real life are considered according to different characteristics of the micro-grid, and the problem of a load scheduling strategy between the micro-grid and a main grid which contain the distributed power supply, the energy storage device, the energy conversion device and the typical load in a region is solved, so that the applicability and the practicability of scheduling are effectively improved, peak clipping and valley filling and ordered power utilization can be realized, and the device is simple and easy to realize.
In addition, the microgrid orderly power utilization scheduling device based on the typical load according to the above embodiment of the present invention may further have the following additional technical features:
further, in an embodiment of the present invention, the obtaining module is further configured to initialize a supply-demand ratio and a real-time power rate, obtain an updated power demand by solving an optimal policy and optimal load scheduling according to the current real-time power rate through the microgrid, issue the updated power demand to a main power grid side, calculate a new supply-demand ratio according to a latest unit load demand of the microgrid side through the main power grid side, and update and distribute the real-time power rate according to a gear of the new supply-demand ratio.
Further, in an embodiment of the present invention, the solving module is further configured to achieve Nash balancing and obtain the optimal ordered power consumption scheduling model when the real-time power rate of the main power grid side and the power demand of the microgrid side are not changed.
Further, in an embodiment of the present invention, the typical loads are classified into an energy storage type load, an adjustable type load, a controllable type load and a base load.
Further, in one embodiment of the present invention, the microgrid comprises a total load of household electricity, industrial electricity, commercial electricity and photovoltaic and wind power generation.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a flowchart of a microgrid orderly power utilization scheduling method based on a typical load according to an embodiment of the present invention;
FIG. 2 is a flow diagram of the operation of an orderly power usage scheduling model according to one embodiment of the present invention;
FIG. 3 is a system diagram of an orderly power usage scheduling model, according to one embodiment of the present invention;
FIG. 4 is a flow chart of an orderly power usage algorithm according to one embodiment of the present invention;
fig. 5 is a schematic structural diagram of a microgrid orderly power utilization scheduling device based on a typical load according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The following describes a microgrid orderly power utilization scheduling method and device based on typical loads according to an embodiment of the present invention with reference to the accompanying drawings, and first, the microgrid orderly power utilization scheduling method based on typical loads according to an embodiment of the present invention will be described with reference to the accompanying drawings.
Fig. 1 is a flowchart of a microgrid orderly power utilization scheduling method based on a typical load according to an embodiment of the present invention.
As shown in fig. 1, the orderly power utilization scheduling method for the microgrid based on the typical load comprises the following steps:
in step S101, a classification of typical loads is obtained, a mathematical model is built according to a type of each load of the microgrid and a current electricity price, and an optimization objective function and a constraint condition are obtained.
In one embodiment of the present invention, the typical load is classified into an energy storage type load, an adjustable type load, a controllable type load and a base load.
It can be understood that, as shown in fig. 2, the embodiment of the present invention establishes a mathematical model based on the classification of typical loads, such as energy storage type, controllable type, adjustable type and base load, according to the load types of each part of the microgrid and the real-time electricity prices issued by the main power grid side, and writes out an optimization objective function and constraint conditions.
Specifically, the loads are first classified into four types: energy storage type load, adjustable type load, controllable type load and basic load. As shown in fig. 3, the total load of four major parts of the microgrid, namely household electricity, industrial electricity, commercial electricity, photovoltaic and wind power generation, is modeled, and is combined with the real-time electricity price published by the main grid to establish an optimal objective function. As shown in fig. 4, the method specifically includes:
(1) the energy storage type load is represented by alpha, can be completely scheduled in the scheduling time, has a reverse power transmission function, such as an energy storage battery, can use the load and can also provide the load for other people to use;
(2) the adjustable load is represented by beta, the load can be completely scheduled in the scheduling time, but the load does not have a power feedback function, for example, the size of the industrial load can be changed, and the load can be stopped and operated in the scheduling time;
(3) the controllable load is represented by gamma, and can be only partially scheduled, namely the running time of the load can be changed, but the load size cannot be changed, and the controllable load also has no reverse power transmission function, for example, a washing machine can be used at any time, but the working power of the washing machine is constant, and the load size cannot be scheduled;
(4) the base load is denoted delta, the fixed load, the load that the user has to use during a certain time each day, is not dispatchable, such as a desk lamp that has to be used at night and a refrigerator that has to be used for 24 hours.
Further, in one embodiment of the present invention, the microgrid comprises a total load of household electricity, industrial electricity, commercial electricity and photovoltaic and wind power generation.
It is understood that a microgrid system comprises four major parts, namely household electricity, industrial electricity, commercial electricity and photovoltaic and wind power generation: the household electricity mainly comprises adjustable and controllable dynamic loads and basic loads; the industrial electricity mainly comprises a basic load and a dynamic load; commercial electricity is mainly a base load, and is not considered because its dynamic load is generally very small; the photovoltaic load and the thermal power generation load mainly comprise a base load and an energy storage type load.
Further, in an embodiment of the present invention, establishing a mathematical model according to the type of each load of the microgrid and the current power rate, and obtaining an optimization objective function and a constraint condition, further includes: initializing supply-demand ratio and real-time electricity price; obtaining an updated power demand by solving an optimal strategy and optimal load scheduling according to the current real-time electricity price through the microgrid, and issuing the updated power demand to the main power grid side; and calculating a new supply-demand ratio through the main power grid side according to the latest unit load demand of the micro power grid side, and updating and distributing real-time electricity prices according to the gears of the new supply-demand ratio.
Specifically, (1) the supply-demand ratio is initialized. The supply-demand ratio r between the main power grid and the micro power gridτFrom a minimum value rminTo a maximum value rmaxDividing into N parts, and sorting from large to small.
(2) First stageAnd (5) initializing the real-time electricity price. According to the supply-demand ratio rτThe real-time electricity price is divided into N grades with unit of yuan/kWh. Setting the lowest electricity price as g0The maximum electricity price is gN-1Real-time electricity price gτ∈[g0,g1,g2,…gn-1,…gN-1]And setting an initial value of the real-time electricity price according to the gear of the supply-demand ratio.
(3) And the micro-grid obtains the updated power demand and distributes the updated power demand to the main power grid side according to the current real-time electricity price and the solving optimal strategy and the optimal load scheduling.
(4) The main power grid side calculates a new supply-demand ratio r according to the latest unit load demand of the micro-power grid sideτUpdating the real-time electricity price g according to the gear of the supply-demand ratioτAnd releasing.
In step S102, the optimal scheduling model is solved according to the game theory until the final result converges to Nash balance, so as to obtain the optimal power load value of each individual unit time, so as to obtain the microgrid ordered power utilization scheduling model based on the typical load.
It can be understood that, as shown in fig. 2, according to a game theory view, by solving the optimal scheduling model, when a final result converges to Nash balance, an optimal power load value of each individual unit time can be obtained, and a micro-grid ordered power utilization scheduling model based on a typical load is obtained.
Further, in an embodiment of the present invention, solving the optimal scheduling model according to a game theory until the final result converges to Nash balance, further includes: when the real-time electricity price at the main power grid side and the electricity demand at the micro-grid side are not changed, Nash balance is achieved, and an optimal ordered electricity utilization scheduling model is obtained.
It can be understood that, as shown in fig. 4, until the real-time electricity price on the main power grid side and the electricity demand on the microgrid side do not change any more, Nash equilibrium is reached, and the optimal ordered electricity utilization scheduling model is obtained.
In step S103, the microgrid side automatically transfers the power load during the peak period to the off-peak period for operation through the microgrid ordered power utilization scheduling model.
It can be understood that after the ordered power utilization scheduling model is obtained, the micro-grid side automatically transfers the power utilization load in the peak period to the low-valley period for operation, so that the power cost can be reduced.
The ordered power utilization scheduling method for the microgrid based on the typical load is further explained by means of a specific embodiment.
The embodiment of the invention is convenient for modeling, and makes the following assumptions:
1) in the minimum scheduling time of electricity prices (set to 1 hour in the embodiment of the present invention), the load sizes of all loads are not changed, and the whole scheduling time region is recorded as a set H ═ 1,2, … τ, … M };
2) for the basic load, the electricity price is kept unchanged all the time, and the electricity price of the basic load is represented by R;
3) for the other three loads, the electricity purchasing price is the same price, and g is usedτRepresenting, wherein τ represents a current time;
4) the subsidy price of photovoltaic and wind power generation is always unchanged and is represented by G. The set of partial quantities of each part of the microgrid is represented by I ═ {1, 2.. I.. N }, each individual part is independent of each other, does not affect each other, and may possess one or more load types.
Firstly, the embodiment of the invention classifies the loads, classifies the loads into 4 types and models:
energy storage type load α: the load can be completely scheduled in the scheduling time, and the device has a reverse power transmission function.
Let the power load of the ith individual in unit time be expressed as
The unit is kWh. The energy storage type load exists only in the photovoltaic and wind power generation part and is related to the generating capacity of the unit, namely the power load in unit time is the generating power of the unit
(assuming that the amount of electricity used is larger than the amount of electricity generated in the present invention), that is
The adjustable load variable is fixed.
Secondly, adjustable load beta: the load can be completely scheduled within the scheduling time, but the reverse power transmission function is not provided.
Let the adjustable load of the ith individual be expressed as the electrical load in unit time
The unit is kWh. The scheduling range is
Wherein
The unit is kWh for rated load. The total load of the electricity in the scheduling time is
The unit is kWh, namely the modeling of the adjustable load variable constraint is as follows:
③ controllable load Gamma: the method can only be partially scheduled, namely the time of load operation can be changed, but the load size cannot be changed, and the method also has no reverse power transmission function.
Let the controllable load of the ith individual be expressed as the electrical load in unit time
The unit is kWh. The scheduling range is
And the load can be divided into an operation state and a non-operation stateState, i.e.
Can only take the value of 0 or
Wherein
The unit is kWh for rated load. The total load of the electricity in the scheduling time is
The unit is kWh, namely the modeling of the adjustable load variable constraint is as follows:
Fourthly, basic load delta: fixed load, the load that the user has to use during a certain time each day, not schedulable.
Let the controllable load of the ith individual be expressed as the electrical load in unit time
The unit is kWh.
And secondly, modeling the electricity charges of four users in the region by taking the lowest total electricity charge in the microgrid as a target. The microgrid load considered in the embodiment of the invention consists of four parts: domestic electricity, industrial electricity, commercial electricity and photovoltaic and wind power generation loads.
Household electricity consumption charge:
the household electricity mainly comprises adjustable and controllable dynamic loads and basic loads.
WhereinBase load electricity charge, by yu,1And then:
wherein u represents the u-th user in the family and has the same meaning as i.
Dynamic charge, with yu,2And then:
wherein p isτThe real-time electricity rate of the current time tau.
So for the home subscriber u, the total electricity charge function is:
however, since the family state is generally the rest state at night, the invention does not consider the input operation of the related equipment for orderly power utilization in the user, so that actually, the other two kinds of dynamic charges except the basic load can be scheduled within 12 hours in the daytime.
Electric charge for industrial power utilization:
the industrial electricity mainly comprises a basic load and a dynamic load. For the industrial user f, the total electricity charge function is:
wherein f represents the f-th user in the industry and has the same meaning as i.
For industrial users, professional staff should manage the operation and suspension of the load equipment for 24 hours, so that for practical purposes, industrial electricity is used for peak load shifting, and most of the load is mainly operated at night.
Third, the electricity charge for commercial use:
commercial power usage is primarily base load and is not considered because its dynamic load is typically very small. For commercial user b, the total electricity charge function is:
wherein b represents the b-th user in the industry and has the same meaning as i.
I.e., commercial power usage, is within the entire microgrid, all loads considered are of an unscheduled part.
Photovoltaic and thermal power generation electric charge:
the part of the load mainly comprises a basic load and an energy storage type load. The basic load is a rated load supporting the operation of the unit when the power generation is not carried out, and the energy storage type load is a total power generation part when the power generation is carried out. The total electricity charge is divided into two parts:
firstly, the power generation of the unit is insufficient for the unit to operate and use, and the consumption state is presented to the outside at the moment
The electricity price is as follows:
wherein s represents the s-th user in the industry and has the same meaning as i.
Secondly, the power generated by the unit can be used by the unit, and the redundant charges can be used by the rest parts of the micro-grid, at the moment
The part of the electricity price of the reverse power transmission needs to be considered, and the electricity price is as follows:
therefore, for the electricity generation type user s, the total electricity fee function is:
the electricity fee of the part is fixed because the electricity consumption of the base load is not changed from the electricity price R of the base load, namely the electricity fee of the commercial electricity is kept unchanged; the energy storage type load is determined by the generating capacity of the unit, is fully utilized in the invention and is determined by external factors such as illumination and wind power, so the electricity price of the energy storage type load is not changed in the invention, and the electricity price of the energy storage type load is fixed, namely the electricity fee of photovoltaic power generation and wind power generation is kept unchanged. The electric charge function y is only related to the electric charges of the adjustable dynamic load and the controllable dynamic load, and the obtained optimization objective function is as follows:
s.t.
The main power grid can determine the power grid electricity price according to the current supply-demand ratio, the load is adjusted through the real-time electricity price, and finally the scheduling of the load of the user is adjusted to be optimal. The supply-demand ratio r between the main power grid and the micro power gridτFrom a minimum value rminTo a maximum value rmaxDividing into N parts, and sorting from large to small. According to the current supply-demand ratio rτWhich segment is located, thereby deciding the corresponding real-time electricity rate.
Microgrid-side overall power demand DτComprises the following steps:
the supply-demand ratio r of the power resourceτComprises the following steps:
in the formula IτThe available power of the main network at tau.
When the real-time electricity price at the main power grid side and the unit load of each individual at the micro-power grid side are not changed any more, the Nash balance is shown to be achieved, and the optimal ordered electricity utilization scheduling model is determined.
In summary, the embodiment of the present invention considers the possibility that wind power and photovoltaic power can generate power to supply load consumption of the microgrid itself under certain conditions for a "micro-main grid" model with photovoltaic and wind power generation in a certain area; the method is combined with the actual situation, a power demand model of the whole microgrid is established on the basis of modeling of typical loads by distinguishing the characteristics of household, commercial and industrial loads, the real-time electricity price is taken as variable quantity, the main power grid side and the microgrid side reach Nash balance, and peak clipping, valley filling and ordered power utilization can be realized while the benefits of the two parties are maximized.
According to the microgrid orderly power utilization scheduling method based on the typical load, the microgrid formed by adding the distributed power supply and the energy storage device at the user side is considered, the typical load classification technology is adopted, most of the microgrid is modeled, the constraint conditions and the running state in real life are considered according to different characteristics of the microgrid, and the problem of load scheduling strategies between the microgrid and a main power grid, wherein the microgrid comprises the distributed power supply, the energy storage device, the energy conversion device and the typical load, is solved, so that the applicability and the practicability of scheduling are effectively improved, peak clipping, valley filling and orderly power utilization can be realized, and the method is simple and easy to realize.
Next, a microgrid orderly power utilization scheduling device based on typical loads according to an embodiment of the present invention is described with reference to the accompanying drawings.
Fig. 5 is a schematic structural diagram of a microgrid orderly power utilization scheduling device based on a typical load according to an embodiment of the present invention.
As shown in fig. 5, the microgrid orderly power utilization scheduling device 10 based on the typical load includes: an acquisition module 100, a solving module 200, and a transfer module 300.
The obtaining module 100 is configured to obtain a classification of typical loads, establish a mathematical model according to a type of each load of the microgrid and a current electricity price, and obtain an optimization objective function and a constraint condition. The solving module 200 is used for obtaining the micro-grid ordered power utilization scheduling model based on the typical load by solving the optimal scheduling model according to the game theory until the final result converges to the Nash balance and obtaining the optimal power utilization load value of each individual unit time. The transfer module 300 is configured to enable the microgrid side to automatically transfer the power load in the peak period to the off-peak period for operation through the microgrid orderly power utilization scheduling model. The device 10 of the embodiment of the invention solves the problem of a load scheduling strategy between a micro-grid and a main grid, wherein the micro-grid comprises a distributed power supply, an energy storage device, an energy conversion device and a typical load in a region, so that the applicability and the practicability of scheduling are effectively improved, peak clipping, valley filling and ordered power utilization can be realized, and the method is simple and easy to realize.
Further, in an embodiment of the present invention, the obtaining module 100 is further configured to initialize the supply-demand ratio and the real-time electricity price, obtain an updated power demand by solving an optimal policy and optimal load scheduling according to the current real-time electricity price through the microgrid, and issue the updated power demand to the main power grid side, calculate a new supply-demand ratio according to a latest unit load demand of the microgrid side through the main power grid side, and update and issue the real-time electricity price according to a gear of the new supply-demand ratio.
Further, in an embodiment of the present invention, the solving module 200 is further configured to achieve Nash balance and obtain an optimal ordered power consumption scheduling model when the real-time power price on the main power grid side and the power consumption demand on the microgrid side are not changed.
Further, in one embodiment of the present invention, the typical load is classified into an energy storage type load, an adjustable type load, a controllable type load and a base load.
Further, in one embodiment of the present invention, the microgrid comprises a total load of household electricity, industrial electricity, commercial electricity and photovoltaic and wind power generation.
It should be noted that the foregoing explanation of the embodiment of the microgrid orderly power utilization scheduling method based on the typical load is also applicable to the microgrid orderly power utilization scheduling device based on the typical load in the embodiment, and details are not described here.
According to the microgrid orderly power utilization scheduling device based on the typical load, the microgrid formed by adding the distributed power supply and the energy storage device at the user side is considered, the typical load classification technology is adopted, most of the microgrid is modeled, the constraint conditions and the running state in real life are considered according to different characteristics of the microgrid, and the problem of load scheduling strategies between the microgrid and a main power grid, wherein the microgrid comprises the distributed power supply, the energy storage device, the energy conversion device and the typical load, is solved, so that the applicability and the practicability of scheduling are effectively improved, peak clipping, valley filling and orderly power utilization can be realized, and the microgrid orderly power utilization scheduling device is simple and easy to realize.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (6)
1. A microgrid ordered power utilization scheduling method based on typical loads is characterized by comprising the following steps:
obtaining the classification of typical loads, establishing a mathematical model for the purpose of minimizing the total power charge in the microgrid according to the type and the current power price of each load of the microgrid, and obtaining an optimization objective function and constraint conditions;
according to the game theory viewpoint, the optimal scheduling model is solved until the final result converges to Nash balance, and the optimal power load value of each individual unit time is obtained, so that the ordered power utilization scheduling model of the micro-grid based on the typical load is obtained; and
through the orderly power utilization scheduling model of little electric wire netting make little electric wire netting side automatic shift the power consumption load of peak hour to the operation of valley hour, total electric charge minimum in little electric wire netting is the target and is established mathematical model according to the type of every load of little electric wire netting and current price of electricity to obtain optimization objective function and constraint condition, further include:
initializing supply-demand ratio and real-time electricity price;
obtaining an updated power demand through solving an optimal strategy and optimal load scheduling according to the current real-time electricity price through the micro-grid, and issuing the updated power demand to the main power grid side;
calculating a new supply-demand ratio through the main power grid side according to the latest unit load demand of the micro power grid side, and updating and distributing real-time electricity prices according to the gears of the new supply-demand ratio;
the microgrid comprises the total load of household electricity, industrial electricity, commercial electricity, photovoltaic and wind power generation.
2. The ordered power utilization scheduling method for the microgrid based on the typical load as claimed in claim 1, wherein the method further comprises the following steps of solving an optimal scheduling model according to a game theory viewpoint until a final result converges to Nash equilibrium:
and when the real-time electricity price of the main power grid side and the electricity demand of the micro-grid side are not changed, the Nash balance is achieved, and the optimal ordered electricity utilization scheduling model is obtained.
3. The microgrid ordered power utilization scheduling method based on typical loads as claimed in claim 1, wherein the classifications of the typical loads include energy storage type loads, adjustable type loads, controllable type loads and base loads.
4. A microgrid orderly power utilization scheduling device based on typical loads is characterized by comprising:
the acquisition module is used for acquiring the classification of typical loads, establishing a mathematical model for the purpose of minimizing the total power charge in the microgrid according to the type of each load of the microgrid and the current power price, and acquiring an optimization objective function and constraint conditions;
the solving module is used for obtaining the optimal power utilization load value of each individual unit time by solving the optimal scheduling model according to the game theory viewpoint until the final result converges to Nash balance, so as to obtain the micro-grid ordered power utilization scheduling model based on the typical load; and
the acquiring module is further used for initializing a supply-demand ratio and a real-time electricity price, obtaining an updated power demand through the microgrid by solving an optimal strategy and optimal load scheduling according to the current real-time electricity price, issuing the updated power demand to the main power grid side, calculating a new supply-demand ratio through the main power grid side according to the latest unit load demand of the microgrid side, and updating and issuing the real-time electricity price according to the gear of the new supply-demand ratio;
the microgrid comprises the total load of household electricity, industrial electricity, commercial electricity, photovoltaic and wind power generation.
5. The microgrid orderly power utilization scheduling device based on typical loads as claimed in claim 4, wherein the solving module is further configured to achieve Nash balancing and obtain the optimal orderly power utilization scheduling model when the real-time electricity price on the main power grid side and the power utilization demand on the microgrid side are not changed.
6. The microgrid ordered power utilization scheduling device based on typical loads as claimed in claim 4, wherein the classifications of the typical loads include energy storage type loads, adjustable type loads, controllable type loads and base loads.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810860460.XA CN110797904B (en) | 2018-08-01 | 2018-08-01 | Micro-grid ordered power utilization scheduling method and device based on typical load |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810860460.XA CN110797904B (en) | 2018-08-01 | 2018-08-01 | Micro-grid ordered power utilization scheduling method and device based on typical load |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110797904A CN110797904A (en) | 2020-02-14 |
| CN110797904B true CN110797904B (en) | 2021-11-16 |
Family
ID=69425329
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810860460.XA Active CN110797904B (en) | 2018-08-01 | 2018-08-01 | Micro-grid ordered power utilization scheduling method and device based on typical load |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110797904B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111600304B (en) * | 2020-06-17 | 2021-11-26 | 广东工业大学 | Building power scheduling method, device and equipment |
| CN113344273B (en) * | 2021-06-08 | 2024-04-19 | 中国农业大学 | Regional power distribution network peak-valley difference adjustment optimization method and system based on building energy |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105790292A (en) * | 2016-01-04 | 2016-07-20 | 国家电网公司 | Optimal control model-based typical load orderly power utilization method |
| CN105846423A (en) * | 2016-03-28 | 2016-08-10 | 华北电力大学 | Method for photovoltaic microgrid energy storage multi-target capacity configuration by taking demand response into consideration |
| CN107330549A (en) * | 2017-06-22 | 2017-11-07 | 华北电力大学 | Multi-energy complementary micro-grid energy management method containing multiagent |
| CN107545325A (en) * | 2017-08-21 | 2018-01-05 | 浙江工业大学 | A kind of more microgrid interconnected operation optimization methods based on game theory |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105550806A (en) * | 2015-12-09 | 2016-05-04 | 国家电网公司 | Typical load ordered power utilization control method and device |
| CN107578182A (en) * | 2017-09-16 | 2018-01-12 | 兰州理工大学 | Micro-grid operational control method is stored up based on light under Demand Side Response |
-
2018
- 2018-08-01 CN CN201810860460.XA patent/CN110797904B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105790292A (en) * | 2016-01-04 | 2016-07-20 | 国家电网公司 | Optimal control model-based typical load orderly power utilization method |
| CN105846423A (en) * | 2016-03-28 | 2016-08-10 | 华北电力大学 | Method for photovoltaic microgrid energy storage multi-target capacity configuration by taking demand response into consideration |
| CN107330549A (en) * | 2017-06-22 | 2017-11-07 | 华北电力大学 | Multi-energy complementary micro-grid energy management method containing multiagent |
| CN107545325A (en) * | 2017-08-21 | 2018-01-05 | 浙江工业大学 | A kind of more microgrid interconnected operation optimization methods based on game theory |
Non-Patent Citations (1)
| Title |
|---|
| 考虑用户满意度的户用型微电网日前优化调度;唐巍等;《高电压技术》;20170131;第43卷(第1期);第140-148页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110797904A (en) | 2020-02-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107958300A (en) | A kind of more microgrid interconnected operation coordinated scheduling optimization methods for considering interactive response | |
| CN109193812A (en) | A kind of garden light storage lotus micro-capacitance sensor economic load dispatching implementation method | |
| CN206041652U (en) | Distributing type photovoltaic power generation energy storage pipe reason control system based on virtual power plant | |
| CN108306288A (en) | A kind of microgrid community distributed energy distribution method based on Demand Side Response | |
| CN108092290A (en) | A kind of microgrid energy collocation method for combining stored energy capacitance configuration and optimization operation | |
| CN108695868A (en) | Power distribution network energy storage addressing constant volume method based on electric power electric transformer | |
| CN105896596B (en) | A kind of the wind power layering smoothing system and its method of consideration Demand Side Response | |
| CN110659788A (en) | Supply and demand balance analysis method and system for user-side comprehensive energy system | |
| CN110752629B (en) | Energy optimization management method for AC/DC hybrid household micro-grid | |
| CN109713666A (en) | It is a kind of based on K-means cluster electricity market under distributed energy storage economic adjusting and control method | |
| CN110797904B (en) | Micro-grid ordered power utilization scheduling method and device based on typical load | |
| CN113988444A (en) | Electricity charge optimization control system and method for light storage system | |
| KR20130074045A (en) | A control method for controlling energy of building based ob microgrid and system for same | |
| CN108512238B (en) | Two-stage optimal scheduling method for smart home based on demand side response | |
| JP2023138478A (en) | Method of controlling battery energy storage system of electric power system with high dynamic load | |
| CN109494813A (en) | A kind of power dispatching method, electronic equipment and storage medium | |
| US9989949B2 (en) | Grid tied, real time adaptive, distributed intermittent power | |
| CN108321916B (en) | Base station with energy cooperation function and energy cooperation method | |
| CN116667337A (en) | Flexible load aggregation modeling method based on distribution network optimization scheduling | |
| CN207053197U (en) | A kind of predictable light storage distributed energy management system | |
| CN112736950B (en) | Public energy storage power station configuration method and system for micro-grid group | |
| CN108493943A (en) | Dispatching method, system, device and the storage medium of more micro-grid system electric energy | |
| CN108683211A (en) | A kind of virtual power plant combined optimization method and model considering distributed generation resource fluctuation | |
| CN114928062A (en) | Demand side response method and device based on shared energy storage equipment | |
| CN110445173B (en) | Multi-agent-based layered multi-microgrid energy management system and scheduling method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |