CN110826210B - Multi-region building virtual power plant modeling and optimization coordination method based on power interconnection - Google Patents
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Abstract
The invention relates to a modeling and optimizing coordination method of a multi-region building virtual power plant based on power interconnection, which is used for realizing aggregation and coordinating optimization of distributed energy sources in a building, and comprises the following steps: (1) designing a basic framework of a multi-zone building virtual power plant; (2) Mathematical modeling is carried out on the constituent elements in the building virtual power plant in each area; (3) designing an objective function of the multi-zone building virtual power plant; (4) And optimally scheduling the internal elements of the multi-region building virtual power plant. Compared with the prior art, the basic framework of the invention can effectively model the scene which is more accordant with the actual building and has more universality.
Description
Technical Field
The invention relates to an aggregation and coordination optimization method for distributed energy sources in a large building, in particular to a modeling and optimization coordination method for a multi-region building virtual power plant based on power interconnection.
Background
With the upgrading of industrial structures and the improvement of living standards of residents, the peak-valley difference of electric power is continuously increased, and peak clipping and valley filling are important problems for improving the safety and stability of an electric power system. The city is used as an energy utilization center of the area, and the construction of the urban energy Internet in the urban area is one of important construction contents for future development of the city. Building is receiving increasing attention as an important component of the urban energy internet. The economic benefit brought by the building is improved unprecedentedly, the economic development drives the improvement of the number of the buildings, and the building area is also increased rapidly. Therefore, the system for controlling building output has important significance for stabilizing distribution network load fluctuation and reducing peak-valley difference.
The virtual power plant technology realizes the aggregation and coordination optimization of different types of distributed energy sources such as distributed power sources, energy storage systems, controllable loads, electric vehicles and the like through advanced technologies such as control, metering and communication. The distributed energy sources, the energy storage system, the flexible load and other diversified resources in the building are integrated in the form of a virtual power plant to participate in comprehensive coordination and optimization of the source network load storage of the power system, so that the purposes of peak clipping and valley filling, load rate improvement and system standby unit capacity reduction can be realized.
The result of the optimized scheduling of the virtual power plant is closely related to the content of the selected elements and the adopted architecture mode. Different modeling approaches and architectural approaches may cause variability in the results. Therefore, it is urgently required to construct a virtual power plant architecture mode and a modeling mode suitable for building objects, and the effectiveness of the optimized dispatching result is guaranteed.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a modeling and optimization coordination method for a multi-region building virtual power plant based on power interconnection.
The aim of the invention can be achieved by the following technical scheme:
the modeling and optimizing coordination method for the multi-region building virtual power plant based on power interconnection is used for realizing aggregation and coordinating optimization of each distributed energy source in a building and comprises the following steps of:
step 1: constructing a basic framework of a multi-region building virtual power plant;
step 2: mathematical modeling is carried out on the constituent elements in the building virtual power plant in each area;
step 3: determining an objective function of the multi-zone building virtual power plant;
step 4: and solving the objective function of the multi-region building virtual power plant by combining the mathematical model corresponding to each internal element to obtain an optimization result and carrying out optimization scheduling.
Further, the basic framework of the multi-region building virtual power plant in the step 1 comprises an electric automobile, energy storage equipment, wind power, photovoltaic and flexible load.
Further, the step 2 includes the following sub-steps:
step 21: constructing mathematical modeling of constraint conditions of the electric automobile;
step 22: constructing mathematical modeling of constraint conditions of energy storage equipment of the electric automobile;
step 23: constructing mathematical modeling of flexible load constraint conditions;
step 24: constructing mathematical modeling of power balance constraint conditions;
step 25: and constructing mathematical modeling of the power interconnection constraint condition.
Further, the constraint condition of the electric vehicle in the step 21 is described as follows:
SOC min ≤SOC i,t,n ≤SOC max
in the method, in the process of the invention,
total charging power of electric vehicle representing the ith zone of the t period, < >>
Representing the charging power of the electric automobile in the ith area of the t period, N i Indicating the number of electric vehicles in the ith region and SOC i,t,n Representing the state of charge, SOC, of an electric vehicle of an nth vehicle in an ith area of a t period min And SOC (System on chip) max Respectively representing the minimum and maximum values of the state of charge of the battery,/->
Indicating the charge state and SOC of the nth vehicle electric vehicle in the ith area of t period when the electric vehicle is charged demand Indicating the state of charge, SOC, required for the electric vehicle to finish charging i,t-1,n The charge state of the electric automobile of the nth vehicle in the ith area of the t-1 period is represented, eta represents the power efficiency and E max The state of charge at the end of charging of the electric vehicle is indicated.
Further, the constraint condition of the electric vehicle energy storage device in the step 22 is described as the following formula:
in the method, in the process of the invention,
and->
Respectively representing the charge and discharge power of the ith area in t period,/->
And->
Respectively representing the maximum charge and discharge power of the ith area in the t period, and the Boolean variable +.>
And->
Respectively indicating whether the energy storage equipment in the ith area of the t period is in a charge and discharge state, if so, setting 1, otherwise, setting 0,>
and->
Respectively representing the upper limit and the lower limit of the storage capacity of the energy storage device in the ith area of the t period,/respectively>
Representing the charge capacity of the energy storage device in the ith area of the t period,/->
And->
Representing the corresponding values of the energy storage device at the beginning and end of the day.
Further, the flexible load constraint condition in the step 23 is described as:
in the method, in the process of the invention,
reducible power indicating that the ith region of t period can be reduced in load, +.>
Maximum reducible power indicating reducible load of the ith region of t period, +.>
The t-period i-th region is indicated to reduce the amount of change in load.
Further, the power balance constraint in the step 24 is described as:
in the method, in the process of the invention,
photovoltaic power representing the ith region of the t period,/->
Representing period tThe wind power of i areas,
electric car power of the ith area in t time period is represented, S represents the total area number, and +.>
Load power of i-th region of t period, < >>
Energy storage device power representing the ith region of the t period,/->
And->
The power input from the j region to the i region in the t period and the power output from the i region to the j region in the t period are respectively represented.
Further, the power interconnection constraint in the step 25 is described as:
in the method, in the process of the invention,
represents the upper limit of the transfer of electrical energy between region i and region j, the Boolean variable +.>
Indicating whether the region i transmits power to the region j in the t period, if so, setting 1, otherwise, setting 0.
Further, the objective function of the multi-zone building virtual power plant in step 3 is described by the following formula:
in the method, in the process of the invention,
maintenance costs of photovoltaic and wind power representing the ith zone of the t period, +.>
Charging maintenance cost of electric vehicle representing ith area of t period, < >>
Maintenance costs of the energy storage device representing the ith zone of the t-period, +.>
Load-reducible compensation cost representing the ith region of the t period, +.>
Representing the trading cost of the power market for the ith region of time t.
Further, the step 4 further includes analyzing the costs of the different multi-zone building virtual power plants in combination with the optimization result, and determining the economical efficiency of the building virtual power plants.
Compared with the prior art, the invention has the following advantages:
(1) Aiming at the problem that the current virtual power plant is less in research and takes buildings as objects, the invention provides a virtual power plant modeling and construction method taking buildings as objects;
(2) In order to better analyze energy conversion, storage and distribution in an energy system, the invention generally adopts the concept of an energy concentrator in a building virtual power plant structure, and wind power, photovoltaics, electric vehicles, flexible loads and energy storage equipment in each building are used as the energy concentrator. The information of each aggregation unit can be better collected, and coordination and optimization can be more effectively carried out;
(3) The method utilizes the power interconnection among the areas to supply power to the heavy-load area from the light-load area, effectively reduces the electric quantity purchased by each area to the electric power market, and can effectively improve the utilization efficiency of electric energy in the virtual power plant while reducing the cost.
Drawings
FIG. 1 is a flow chart of a method for modeling and optimizing coordination of a multi-zone building virtual power plant based on power interconnection;
FIG. 2 is a block diagram of an energy hub provided by the present invention;
FIG. 3 is a block diagram of a multi-zone building virtual power plant provided by the present invention;
FIG. 4 is a schematic diagram of residential area output change in an embodiment;
FIG. 5 is a schematic diagram of a change in commercial district output in an embodiment;
FIG. 6 is a schematic diagram of a power interconnect variation in an embodiment;
FIG. 7 is a graph showing the variation of load fluctuation after the method of the present invention is used in the examples.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
Examples
Referring to fig. 1, a power interconnection-based multi-region building virtual power plant modeling and optimization coordination method is used for optimizing and scheduling output of demand side resources in a building, wherein the demand side resources refer to: renewable energy sources, electric vehicles, flexible loads, and energy storage devices.
The invention discloses a modeling and optimizing coordination method of a multi-region building virtual power plant based on power interconnection, which comprises the following steps:
(1) The basic architecture of a multi-zone building virtual power plant is designed, in particular:
compared with Shan Dong building virtual power plants, the virtual power plants constructed by the multiple buildings can realize energy complementation of all areas, coordinate the output of the power generation units of all areas, effectively reduce the net cost of the virtual power plants, and have obvious energy complementation effect due to the difference of peak-valley periods of different types of buildings. In order to better analyze energy conversion, storage and distribution in an energy system, the concept of an energy hub is generally adopted in a virtual power plant structure, and wind power, photovoltaic, electric vehicles and energy storage equipment in each building are used as an energy hub as shown in fig. 2. Each aggregation unit in the virtual power plant is coordinated and controlled through an energy management system, and when the virtual power plant operates, the energy management system collects information of each unit in the power market and the energy concentrator and predicts the electricity price of the power market, the fan/photovoltaic output and the electric load according to the information. And then, according to the prediction and the information of each unit in the energy hub, the energy management system formulates a control strategy and sends a scheduling instruction to control each unit to operate. When a certain area is in electric energy shortage, other areas supply power to the area through the inter-area interconnection line. In this example, a residential building and a commercial building are taken to construct a multi-region building virtual power plant, and the structure diagram is shown in fig. 3.
(2) Mathematical modeling is carried out on the constituent elements in the building virtual power plant in each area:
the step (2) comprises the following steps:
(21) Establishing electric automobile restraint:
SOC min ≤SOC i,t,n ≤SOC max
in the method, in the process of the invention,
total charging power of electric vehicle representing the ith zone of the t period, < >>
Representing the charging power of the electric automobile in the ith area of the t period, N i Indicating the number of electric vehicles in the ith region and SOC i,t,n Representing the state of charge, SOC, of an electric vehicle of an nth vehicle in an ith area of a t period min And SOC (System on chip) max Respectively representing the minimum and maximum values of the state of charge of the battery,/->
Indicating the charge state and SOC of the nth vehicle electric vehicle in the ith area of t period when the electric vehicle is charged demand Indicating the state of charge, SOC, required for the electric vehicle to finish charging i,t-1,n The charge state of the electric automobile of the nth vehicle in the ith area of the t-1 period is represented, eta represents the power efficiency and E max The state of charge at the end of charging of the electric vehicle is indicated.
(22) Establishing constraint of energy storage equipment of the electric automobile:
in the method, in the process of the invention,
and->
Respectively representing the charge and discharge power of the ith area in t period,/->
And->
Respectively representing the maximum charge and discharge power of the ith area in the t period, and the Boolean variable +.>
And->
Respectively indicating whether the energy storage equipment in the ith area of the t period is in a charge and discharge state, if so, setting 1, otherwise, setting 0,>
and->
Respectively representing the upper limit and the lower limit of the storage capacity of the energy storage device in the ith area of the t period,/respectively>
Representing the charge capacity of the energy storage device in the ith area of the t period,/->
And->
Representing the corresponding values of the energy storage device at the beginning and end of the day.
(23) Establishing a flexible load constraint:
in the method, in the process of the invention,
reducible power indicating that the ith region of t period can be reduced in load, +.>
Maximum reducible power indicating reducible load of the ith region of t period, +.>
The t-period i-th region is indicated to reduce the amount of change in load.
(24) Establishing a power balance constraint:
in the method, in the process of the invention,
photovoltaic power representing the ith region of the t period,/->
Representing the wind power of the ith region of the t period,
representing tElectric car power in the ith zone of the period, S represents the total zone number, +.>
Load power of i-th region of t period, < >>
Energy storage device power representing the ith region of the t period,/->
And->
The power input from the j region to the i region in the t period and the power output from the i region to the j region in the t period are respectively represented.
(25) Establishing power interconnection constraint:
the power interconnection constraint condition in the step 25 is described as follows:
in the method, in the process of the invention,
represents the upper limit of the transfer of electrical energy between region i and region j, the Boolean variable +.>
And (3) indicating whether the region i transmits electric energy to the region j in the t period, if so, setting 1, otherwise, setting 0, and ensuring that the transmission direction of the power in any period is unique by using the Boolean variable.
(3) Designing an objective function of the multi-zone building virtual power plant, wherein the step (3) aims at minimizing the economic cost of the multi-zone building virtual power plant, and specifically comprises the following steps:
in the method, in the process of the invention,
maintenance costs of photovoltaic and wind power representing the ith zone of the t period, +.>
Charging maintenance cost of electric vehicle representing ith area of t period, < >>
Maintenance costs of the energy storage device representing the ith zone of the t-period, +.>
Load-reducible compensation cost representing the ith region of the t period, +.>
Representing the trading cost of the power market for the ith region of time t.
(4) And carrying out optimal scheduling on the internal elements of the multi-region building virtual power plant to obtain an optimal result. Step (4) uses three schemes for comparison, proving the economic superiority of the scheme. Specifically:
two points are embodied through different schemes, namely, the economic benefit brought by the coordination and optimization of distributed energy sources in a building by adopting a virtual power plant technology is verified; and secondly, verifying the economic benefit brought by combining a plurality of buildings.
Table 1 scheme comparison
As shown in table 1, three schemes are used for optimal scheduling, and the cost is shown in table 2:
table 2 cost comparison
The electric automobile charging power of each building, the transaction amount with the electric market and the power transmission among each building after the dispatching optimization are shown in fig. 4 to 6. The load profile of the system after scheduling is shown in fig. 7.
As can be seen from fig. 4 to 6, since the photovoltaic has insufficient power generation at night, the power generation units in the residential building and the commercial building cannot meet the demands of the load units in the virtual power plant at 1-3 time periods and 24 th time, and therefore, electric energy needs to be purchased from the electric power market, and almost no power is transmitted between the virtual power plants. At the 4-9 time period and the 23 rd time, as the generated energy of the generating unit inside each virtual power plant remains, each virtual power plant sells the remaining electric quantity to the electric power market in a mode of trading with the electric power market, and meanwhile, the energy storage equipment starts to be charged; at this point, there is still no power interconnection between the virtual power plants, as the load of each virtual power plant meets the demand. In the period of 10-22, because the electricity consumption of the commercial building is too large, the electricity consumption requirement of the commercial building cannot be met only by the electricity generating units in the virtual power plant, and the photovoltaic and wind power in the residential building can meet the load requirement of the commercial building, and a certain amount of generated energy still remains. At this time, the resident building supplies power to the commercial building to reduce the amount of electricity purchased by the commercial building. Meanwhile, the energy storage equipment is mainly discharged at the moment of low electricity price because the electricity price at the moment is higher, the load of a user is reduced, and the compensation price is smaller than the price of electricity purchased from the electric power market although the user is given a certain compensation, so that the running cost of the virtual power plant is reduced.
The electric automobile of the residential building is selected to be charged in the period 22-9, and the charging in the period is selected to effectively reduce the running cost of the virtual power plant because the electricity price is lower in the period; meanwhile, the total load is smaller in the period, and the effects of peak clipping and valley filling can be achieved to a certain extent. The business building has the time of going up and down, so that the time of dispatching is not 24 hours in the whole day, but 8-21 hours, and therefore, the electric automobile in the business building is charged at the scattered moment with lower electricity price, and the burden of the peak period is also reduced to a certain extent while the cost is reduced.
Building virtual power plants achieve peak load shedding at 10-13 and 16-20 times of the system and increase load levels at 1-6 valley periods. The peak system load occurred at 13 pm and 20 pm, reaching 3356.2kW and 3544.4kW, respectively. The peak load after adjustment occurred at 13 pm and 20 pm, at 3141.6kW and 3249.4kW. The implementation of the building virtual power plant reduces the system peak load level by 6.39% and 8.32%, respectively. And when the system primary valley value appears in 6 a morning, the load level of the building virtual power plant is increased from 936.8kW to 1074.1kW and is increased by 14.7% when the building virtual power plant participation valley value still appears in 6 a morning.
The average level of the original load of the system is 2340kW, and the average level of the load of the system after the building virtual power plant is implemented is 2340kW, and no significant change occurs. This is because the load aggregator fully considers the electricity demand of the user when adjusting the electricity plans of the power user and the electric vehicle, and guides the peak shift electricity consumption through the power price change. Therefore, the building virtual power plant plays a role in adjusting the system load curve by peak clipping and valley filling while ensuring that the electric energy requirement of a user is met.
While the invention has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (4)
1. The modeling and optimizing coordination method for the multi-region building virtual power plant based on the power interconnection is used for realizing aggregation and coordinating optimization of all distributed energy sources in the building and is characterized by comprising the following steps of:
step 1: constructing a basic framework of a multi-region building virtual power plant;
step 2: mathematical modeling is carried out on the constituent elements in the building virtual power plant in each area;
step 3: determining an objective function of the multi-zone building virtual power plant;
step 4: solving the objective function of the multi-region building virtual power plant by combining the mathematical model corresponding to each internal element to obtain an optimized result and performing optimized scheduling;
the step 2 comprises the following sub-steps:
step 21: constructing mathematical modeling of constraint conditions of the electric automobile;
step 22: constructing mathematical modeling of constraint conditions of energy storage equipment of the electric automobile;
step 23: constructing mathematical modeling of flexible load constraint conditions;
step 24: constructing mathematical modeling of power balance constraint conditions;
step 25: constructing mathematical modeling of power interconnection constraint conditions;
the constraint condition of the electric vehicle in the step 21 is described as follows:
SOC min ≤SOC i,t,n ≤SOC max
in the method, in the process of the invention,
represents the ith region of the t periodTotal charging power of electric vehicle, +.>
Representing the charging power of the electric automobile in the ith area of the t period, N i Indicating the number of electric vehicles in the ith region and SOC i,t,n Representing the state of charge, SOC, of an electric vehicle of an nth vehicle in an ith area of a t period min And SOC (System on chip) max Representing the minimum and maximum values of the battery state of charge respectively,
indicating the charge state and SOC of the nth vehicle electric vehicle in the ith area of t period when the electric vehicle is charged demand Indicating the state of charge, SOC, required for the electric vehicle to finish charging i,t-1,n The charge state of the electric automobile of the nth vehicle in the ith area of the t-1 period is represented, eta represents the power efficiency and E max The charge state when the electric automobile finishes charging is represented;
the constraint condition of the energy storage device of the electric automobile in the step 22 is described as follows:
in the method, in the process of the invention,
and->
Respectively representing the charge and discharge power of the ith area in t period,/->
And->
Respectively representing the maximum charge and discharge power of the ith area in the t period, and the Boolean variable +.>
And->
Respectively indicating whether the energy storage equipment in the ith area of the t period is in a charge and discharge state, if so, setting 1, otherwise, setting 0,>
and->
Respectively representing the upper limit and the lower limit of the storage capacity of the energy storage device in the ith area of the t period,/respectively>
Representing the charge capacity of the energy storage device in the ith area of the t period,/->
And->
Representing the corresponding value of the energy storage device at the beginning and the end of a day;
the flexible load constraint in step 23 is described by the formula:
in the method, in the process of the invention,
reducible power indicating that the ith region of t period can be reduced in load, +.>
Maximum reducible power indicating reducible load of the ith region of t period, +.>
Indicating the variable amount of load reducible in the ith region of the t period;
the power balance constraint in the step 24 is described as:
in the method, in the process of the invention,
photovoltaic power representing the ith region of the t period,/->
Wind power generation representing ith region of t periodRate of->
Electric car power of the ith area in t time period is represented, S represents the total area number, and +.>
Load power of i-th region of t period, < >>
Energy storage device power representing the ith region of the t period,/->
And->
Respectively representing the power input from the j region to the i region in the t period and the power output from the i region to the j region in the t period;
the power interconnection constraint condition in the step 25 is described as follows:
in the method, in the process of the invention,
represents the upper limit of the transfer of electrical energy between region i and region j, the Boolean variable +.>
Indicating whether zone i transmits power to zone j for period t, if so, setting 1, otherwise, setting 0,/-for period t>
And->
The power input from the j region to the i region in the t period and the power output from the i region to the j region in the t period are respectively represented.
2. The method for modeling and optimizing coordination of the multi-region building virtual power plant based on power interconnection according to claim 1, wherein the basic framework of the multi-region building virtual power plant in the step 1 comprises electric vehicles, energy storage equipment, wind power, photovoltaics and flexible loads.
3. The method for modeling and optimizing coordination of a multi-zone building virtual power plant based on power interconnection according to claim 1, wherein the objective function of the multi-zone building virtual power plant in step 3 is described by the following formula:
in the method, in the process of the invention,
maintenance costs of photovoltaic and wind power representing the ith zone of the t period, +.>
Charging maintenance cost of electric vehicle representing ith area of t period, < >>
Maintenance costs of the energy storage device representing the ith zone of the t-period, +.>
Load-reducible compensation cost representing the ith region of the t period, +.>
Representing the trading cost of the power market for the ith region of time t.
4. The method for modeling and optimizing coordination of multi-zone building virtual power plants based on power interconnection according to claim 1, wherein the step 4 further comprises analyzing the cost of different multi-zone building virtual power plants by combining the optimizing result to determine the economical efficiency of the building virtual power plants.
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| CN110225075A (en) * | 2019-03-25 | 2019-09-10 | 北京快电科技有限公司 | A kind of building energy internet wisdom operation cloud operating system |
| CN110245790A (en) * | 2019-05-31 | 2019-09-17 | 国网上海市电力公司 | The accurate adjusting method of region load based on virtual plant technology |
| JP2019165566A (en) * | 2018-03-20 | 2019-09-26 | 本田技研工業株式会社 | Management apparatus, method, program and management system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107046301A (en) * | 2017-04-18 | 2017-08-15 | 国网上海市电力公司 | The layered multi-stage power grid regulation system and method for building load cluster |
| JP2019165566A (en) * | 2018-03-20 | 2019-09-26 | 本田技研工業株式会社 | Management apparatus, method, program and management system |
| CN110225075A (en) * | 2019-03-25 | 2019-09-10 | 北京快电科技有限公司 | A kind of building energy internet wisdom operation cloud operating system |
| CN110188950A (en) * | 2019-05-30 | 2019-08-30 | 三峡大学 | Virtual plant supply side and Demand-side Optimized Operation modeling method based on multi-agent technology |
| CN110245790A (en) * | 2019-05-31 | 2019-09-17 | 国网上海市电力公司 | The accurate adjusting method of region load based on virtual plant technology |
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