CN115222219A - Optimal scheduling method and device for electric boiler system participating in power grid frequency modulation service - Google Patents
Optimal scheduling method and device for electric boiler system participating in power grid frequency modulation service Download PDFInfo
- Publication number
- CN115222219A CN115222219A CN202210742249.4A CN202210742249A CN115222219A CN 115222219 A CN115222219 A CN 115222219A CN 202210742249 A CN202210742249 A CN 202210742249A CN 115222219 A CN115222219 A CN 115222219A
- Authority
- CN
- China
- Prior art keywords
- heat
- boiler system
- frequency modulation
- electric boiler
- scheduling
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 46
- 230000004044 response Effects 0.000 claims abstract description 129
- 230000008901 benefit Effects 0.000 claims abstract description 28
- 230000005611 electricity Effects 0.000 claims abstract description 14
- 238000005338 heat storage Methods 0.000 claims description 32
- 230000003827 upregulation Effects 0.000 claims description 17
- 230000003828 downregulation Effects 0.000 claims description 13
- 238000005457 optimization Methods 0.000 claims description 11
- 238000010438 heat treatment Methods 0.000 claims description 9
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 9
- 230000007613 environmental effect Effects 0.000 claims description 6
- 230000017525 heat dissipation Effects 0.000 claims description 3
- 230000004043 responsiveness Effects 0.000 claims description 3
- 238000007599 discharging Methods 0.000 claims description 2
- 230000001360 synchronised effect Effects 0.000 claims description 2
- 230000008569 process Effects 0.000 description 8
- 238000010586 diagram Methods 0.000 description 7
- 230000033228 biological regulation Effects 0.000 description 6
- 230000007246 mechanism Effects 0.000 description 5
- 238000005265 energy consumption Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 230000002068 genetic effect Effects 0.000 description 4
- 230000003993 interaction Effects 0.000 description 4
- 239000002245 particle Substances 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 230000005284 excitation Effects 0.000 description 3
- 239000000463 material Substances 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 230000006698 induction Effects 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000002441 reversible effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06313—Resource planning in a project environment
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0206—Price or cost determination based on market factors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The invention provides an optimal scheduling method and device for participating in power grid frequency modulation service of an electric boiler system, which comprises the following steps: predicting the electric energy marginal price of the electric boiler system for purchasing electricity from the power grid and the clear price of the frequency modulation service when the electric boiler system participates in the frequency modulation service of the power grid in each scheduling period of the operation day; obtaining a heat demand side response plan of each scheduling time period on the operating day according to the electric energy marginal price; establishing a corresponding first profit model when not participating in the power grid frequency modulation service and a corresponding second profit model when participating in the power grid frequency modulation service; determining a final scheduling scheme corresponding to the maximum profit of the electric boiler system; and scheduling the electric boiler system according to the final scheduling scheme. Therefore, on the premise that the electric boiler system meets the heat load required by the heat demand side, the residual frequency modulation resources are participated in the management of the power grid demand side, the frequency modulation service is provided for the power grid, meanwhile, the benefit of the electric boiler system is maximized, the operation safety of the power grid is improved, and the overall benefit of the electric boiler system is improved.
Description
Technical Field
The invention relates to the technical field of electric boilers, in particular to an optimal scheduling method for an electric boiler system to participate in power grid frequency modulation service and an optimal scheduling device for the electric boiler system to participate in the power grid frequency modulation service.
Background
With the reduction of limited energy and the price rise greatly, the heat supply demand of the heat demand side can be met by utilizing the quick response capability and the demand side response technology of the heat supply boiler as emerging electric boiler equipment and by optimizing arrangement and timely adjusting the operation mode.
In the related art, there is a technology of applying an electric boiler including a heat storage device to a grid regulation demand, however, the technology does not consider the profit on the electric boiler side, and easily affects the heat supply on the heat demand side when participating in the grid regulation, and thus, the operation effect is poor.
Disclosure of Invention
The invention provides the following technical scheme for solving the problems that the income of the electric boiler side is not considered in the related technology and the heat supply of the heat demand side is easily influenced when the electric boiler participates in the power grid regulation.
The embodiment of the first aspect of the invention provides an optimal scheduling method for participating in power grid frequency modulation service by an electric boiler system, wherein the electric boiler system comprises an electric boiler and a heat storage device, and the method comprises the following steps: predicting the electric energy marginal price purchased by the electric network from the electric power during each scheduling period of the operating day and the clearing price of the frequency modulation service when the electric boiler system participates in the frequency modulation service of the electric network during each scheduling period of the operating day; obtaining a thermal demand side response plan of each scheduling time period of the operation day according to the electric energy marginal price; establishing a first profit model corresponding to the electric boiler system when not participating in the power grid frequency modulation service and a second profit model corresponding to the electric boiler system when participating in the power grid frequency modulation service; determining a final scheduling scheme corresponding to the maximum profit of the electric boiler system according to the electric energy marginal price, the frequency modulation service clearing price, the heat demand side response plan, the first profit model and the second profit model, wherein the final scheduling scheme comprises a maximum profit final value of the electric boiler system, a heat final value provided by the electric boiler system to the heat demand side in each scheduling period and an electric power final value provided by an electric network; and scheduling the electric boiler system according to the final scheduling scheme.
In addition, the method for optimally scheduling the electric boiler system participating in the grid frequency modulation service according to the above embodiment of the present invention may further have the following additional technical features.
According to one embodiment of the invention, predicting the marginal price of electric energy purchased from the power grid by the electric boiler system in each dispatching period of the operation day and the clearing price of the frequency modulation service when the electric boiler system participates in the frequency modulation service of the power grid in each dispatching period of the operation day comprises the following steps: acquiring historical data of a power auxiliary service market, wherein the historical data comprises first historical electric power of a power grid requiring frequency modulation service and second historical electric power of the power grid actually providing the frequency modulation service; and predicting the electric energy marginal price purchased from the power grid by the electric boiler system in each scheduling period of the operating day and the frequency modulation service clearing price when the electric boiler system participates in the power grid frequency modulation service in each scheduling period of the operating day according to the acquired historical data.
According to an embodiment of the invention, determining a final scheduling scheme corresponding to the profit maximization of the electric boiler system according to the electric energy marginal price, the frequency modulation service clearing price, the heat demand side response plan, the first profit model and the second profit model comprises: determining the heat supply amount required by each heat user at the heat demand side in each scheduling period based on the heat demand side response plan, wherein the heat demand response plan comprises heat demand response temperature; determining the response capacity of the heat demand side in each scheduling period of a running day according to the heat supply amount required by each heat user in each scheduling period, wherein the response capacity comprises an up-regulation response capacity and a down-regulation response capacity; inputting the electric energy marginal price into the first profit model, and performing optimization solution on the first profit model through a preset algorithm with the response capacity as a constraint condition and with the profit maximization as a target to obtain a maximum profit initial value of the electric boiler system, a heat initial value provided by the electric boiler system to a heat demand side at each scheduling period and an electric power initial value provided by an electric network, wherein the heat initial value is between the up-regulation response capacity and the down-regulation response capacity; inputting the frequency modulation service clearing price, the heat initial value and the electric power initial value into the second profit model, optimizing the second profit model by using the response capacity as a constraint condition through a preset algorithm and aiming at maximizing profits to obtain a maximum profit final value of the electric boiler system, a heat final value provided by the electric boiler system to a heat demand side at each scheduling period and an electric power final value provided by a power grid, wherein the heat final value is between the up-regulation response capacity and the down-regulation response capacity.
According to one embodiment of the invention, the determining the heat supply amount required by each heat user on the heat demand side in each scheduling period based on the heat demand side response plan comprises the following steps: acquiring external environment factor data and internal human factor data, wherein the external environment factor data comprises the current temperature, and the internal human factor data comprises the heat required by a hot user; determining the heat capacity of the building space to which each heat user belongs; in each scheduling period, determining a plurality of heats corresponding to the building space to which the heat user belongs according to the external environmental factor and the internal human factor data, wherein the plurality of heats comprise heat transferred by each wall surface, heat radiated by a window, heat transferred to indoor air by an indoor thermal disturbance factor and indoor heat brought by indoor and outdoor air or adjacent room air in an exchange manner; and determining the heat supply amount required by each heat user in each scheduling time interval at the heat demand response temperature according to the heat demand response temperature, the current temperature, the heat capacity and the plurality of heat quantities.
According to one embodiment of the present invention, the heating load required by each thermal consumer at the thermal demand response temperature for each scheduling period is calculated according to the following formula:
T a ＝T 1 -T 2
wherein, T 1 Is the heat demand response temperature, T 2 Is said current temperature, T a Is the difference between the thermal demand response temperature and the current temperature, U is the number of building walls, V is the heat capacity of the building space to which the thermal user belongs, Q ws,u,t Heat transferred for the u-th wall surface during the period t, Q win,t Heat radiated through the window for a period of t, Q con,t Heat transferred to the indoor air for the indoor thermal disturbance factor during the period t, Q tra,t Heat brought in by indoor or outdoor air or air exchange in adjacent rooms during time t, Q offer,t The heat supply quantity required by the heat user in the time period t under the demand response plan.
According to one embodiment of the invention, the thermal demand response temperature comprises an optimal thermal comfort temperature, a maximum allowable thermal comfort temperature and a minimum allowable thermal comfort temperature, and the response capacity of the thermal demand side at each scheduling period on the operation day is determined according to the following formula:
wherein G is the number of hot users, Q t,up For the up-regulation response capability of the heat demand side in the period t, Q t,down For turndown responsiveness of the heat demand side during time t, Q g,t,best The heat supply quantity, Q, required by the g-th heat user at the optimal heat comfort temperature in the period t g,t,Tmax The required heat supply at the maximum allowable thermal comfort temperature in the t period of the g-th thermal user, Q g,t,Tmin The minimum allowable heat supply amount at the t period of the g-th heat user is the required heat supply amount at the temperature of the thermal comfort level.
According to one embodiment of the invention, the first benefit model is:
M 1 ＝I 2 -C 1 -C 2 -C 3
wherein M is 1 As a first revenue model, I 2 For the heating benefits of the electric boiler system when providing thermal services to the heat demand side, C 1 Cost of electricity purchase required to provide frequency modulation service to the grid and thermal service to the thermal demand side for said electric boiler system, C 2 For the heat storage cost, which is the sum of the heat dissipation cost and the heat transmission loss cost of the electric boiler system in the non-operating state, C 3 The cost of the heat supply network is the cost of the power consumption expense of the circulating water pump of the heat supply network in the operation of the electric boiler system;
the second revenue model is:
M 2 ＝I 1 +I 2 -C 1 -C 2 -C 3
wherein M is 2 As a second profit model, I 1 And the frequency modulation benefit is generated when the electric boiler system participates in the power grid frequency modulation service.
According to one embodiment of the present invention, the frequency modulation gain is:
I 1 ＝I cap +I mil
wherein H is the total scheduling period of the operation day, and beta isFrequency modulation performance index, sigma is frequency modulation mileage ratio, delta t is time step length, I cap For gain of frequency-modulated capacity, I mil For frequency-modulated mileage earnings, p cap,t For predicted tuned capacity clearing price, p, of time t mil，t Clearing price, P, for predicted time-t-period frequency-modulated mileage offer,t Frequency modulation capacity provided for the t period.
According to one embodiment of the invention, the heating gain is:
h is the total scheduling time interval of the operation day, G is the number of hot users, delta t is the time step length, and Q g,t,best The heat supply quantity required by the optimal heat comfortable temperature in the period t of the g-th heat user, Q g,t Amount of heat supplied to g users for period t, p heat For unit price of heat supply, eta g The t-period elastic compensation coefficient of the g users.
According to one embodiment of the invention, the electricity purchase cost is:
where H is the total scheduling period of the day of operation, p grid,t For predicted marginal price of electric energy, p, of time t of day of operation eb,t And the delta t is the time step for the electric power exchanged between the electric boiler and the power grid in the period of t.
According to one embodiment of the invention, the heat storage cost is:
wherein H is the total scheduling time interval of the operation day, delta t is the time step, p heat Is a heat power unit heat price, Q sto,t Is the heat storage capacity of the heat storage device in the period t, mu s to,loss Is the heat loss rate of the heat storage device, mu sto,in For the charging efficiency of the heat storage device, mu sto,out For heat-releasing efficiency of the heat-storage device, Q sto,in,t And Q sto,out,t The heat charging and discharging power of the heat storage device is t time.
According to one embodiment of the invention, the heat net cost is:
wherein H is the total scheduling time interval of the operation day, delta t is the time step, and omega wp For the power and heat consumption ratio of water pump, p grid,t For predicted marginal price of electric energy, Q, for time period t of operation day wp,t The thermal power transmitted by the water pump in the period t.
The embodiment of the second aspect of the invention provides an optimized scheduling device for an electric boiler system to participate in grid frequency modulation service, wherein the electric boiler system comprises an electric boiler and a heat storage device, and the device comprises: the prediction module is used for predicting the electric energy marginal price purchased from the power grid by the electric boiler system in each scheduling period of the operating day and the frequency modulation service clearing price when the electric boiler system participates in the frequency modulation service of the power grid in each scheduling period of the operating day; the first determining module is used for obtaining a thermal demand side response plan of each scheduling time interval on the operating day according to the electric energy marginal price; the establishing module is used for establishing a corresponding first profit model when the electric boiler system does not participate in the power grid frequency modulation service and a corresponding second profit model when the electric boiler system participates in the power grid frequency modulation service; a second determining module, configured to determine a final scheduling scheme corresponding to the profit maximization of the electric boiler system according to the electric energy marginal price, the frequency modulation service clearing price, the thermal demand side response plan, the first profit model, and the second profit model, where the final scheduling scheme includes a maximum profit end value of the electric boiler system, a thermal end value provided by the electric boiler system to a thermal demand side at each scheduling period, and an electric power end value provided to an electric grid; and the scheduling module is used for scheduling the electric boiler system according to the final scheduling scheme.
According to the technical scheme of the embodiment of the invention, the electric energy marginal price and the frequency modulation service clearing price are predicted, the heat demand side response plan is obtained according to the electric energy marginal price, two profit models of the electric boiler system are established, and then the electric boiler system is determined to participate in the frequency modulation of the power grid and provide heat service to the heat demand side when the profit is the maximum according to the electric energy marginal price, the frequency modulation service clearing price, the heat demand side response plan and the two profit models. Therefore, on the premise that the electric boiler system meets the heat load required by the heat demand side, the residual frequency modulation resources are participated in the management of the power grid demand side, the frequency modulation service is provided for the power grid, meanwhile, the benefit of the electric boiler system is maximized, the operation safety of the power grid is improved, and the overall benefit of the electric boiler system is also improved.
Drawings
Fig. 1 is a schematic diagram of a mechanism for participating in power grid demand side management by an electric boiler system according to an embodiment of the present invention.
FIG. 2 is a schematic diagram of a supply and demand interaction process of the electric boiler system according to the embodiment of the invention.
Fig. 3 is a flowchart of an optimal scheduling method for participating in grid frequency modulation service of an electric boiler system according to an embodiment of the present invention.
FIG. 4 is a schematic diagram of an optimized schedule for an electric boiler system according to an example of the present invention.
Fig. 5 is a block diagram illustrating an optimized scheduling device for participating in grid frequency modulation service of an electric boiler system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Fig. 1 is a schematic diagram of a mechanism for participating in power grid demand side management by an electric boiler system according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a supply and demand interaction process of an electric boiler system according to an embodiment of the present invention.
In order to provide an optimal scheduling method for an electric boiler system to participate in power grid frequency modulation service, an electric boiler system participation power grid demand side management mechanism is firstly established, as shown in fig. 1, and the mechanism is as follows: the method comprises the steps that a power grid regulation and control center sends a frequency modulation instruction, an electric boiler operator receives the frequency modulation instruction to transfer demand side frequency modulation resources (the active power consumed by an electric boiler is adjustable according to a heat demand side), active regulation is completed, a heat source side (the electric boiler) and a power grid supply and demand are interactively completed, the heat demand side regulates demand side response according to self required heat load and feeds the response back to the electric boiler operator, and the electric boiler operator adopts an excitation compensation mode to formulate a response policy according to the supply and demand conditions of a power system.
It should be noted that the main role of the power grid frequency modulation service is that the power regulation and control center sends an instruction for increasing or decreasing the available output through Automatic Generation Control (AGC) when the frequency modulation resource meets the load change, so as to maintain the balance of the power system.
The heat demand side response means that the heat source side performs economic induction on the heat demand side in a mode of directly compensating for reduced load or changing heat energy price, and the inherent heat using behavior of the heat demand side is changed, so that the heat source side resource is transferred to perform power grid frequency modulation. The excitation compensation can be made in a direct compensation manner, i.e. the more heat load is transferred on the heat demand side, the more economic compensation is given.
Then, a supply and Demand interaction mode based on HDR (Heat Demand Response) is established as shown in fig. 2, the Heat source side responds to the Heat source side by changing the inherent Heat energy consumption mode of the Heat Demand side in an excitation compensation mode, and the Heat source side electric boiler further responds to the scheduled operation of the electric power system, so as to realize the frequency modulation of the electric power system by the Heat Demand side.
As shown in fig. 2, firstly, an electric boiler operator makes an elastic compensation scheme for each scheduling period according to the frequency modulation service clearing price and the electric energy marginal price of each scheduling period of the operating day predicted by the historical data of the electric power auxiliary service market, and a thermal demand side may be, for example, a residential building including a plurality of buildings, each building including n thermal users. And the heat demand side formulates a heat demand response plan according to the elastic compensation scheme, and finally, an operator determines the heat supply amount at a given temperature according to the demand response plan and predicts the response capacity of the heat demand side, optimizes the operation daily output arrangement of the electric heat storage boiler, and determines the actual call response capacity and actual compensation of the operation day.
On the basis of fig. 1 and fig. 2, an embodiment of the present invention provides an optimal scheduling method for an electric boiler system to participate in a grid frequency modulation service.
Fig. 3 is a flowchart of an optimal scheduling method for participating in grid frequency modulation service of an electric boiler system according to an embodiment of the present invention.
The electric boiler system of the embodiment of the invention comprises an electric boiler, a heat storage device, a heat supply pipeline and each heat user at a heat demand side.
The execution main body of the optimal scheduling method for the electric boiler system participating in the power grid frequency modulation service can be an electric boiler operator.
As shown in fig. 3, the method for optimally scheduling the participation of the electric boiler system in the grid frequency modulation service includes the following steps S1 to S5.
S1, forecasting electric energy marginal price purchased by the electric power grid from the electric power grid in each dispatching time period of an operation day and clearing price of frequency modulation service when the electric boiler system participates in the frequency modulation service of the electric power grid in each dispatching time period of the operation day.
Wherein, the operation day may refer to 24 hours, and each scheduling period may be 1 hour.
Specifically, the electric energy marginal price of the electric boiler system for purchasing electricity from the power grid in each scheduling period of the operation day and the frequency modulation service clearing price when the electric boiler system participates in the power grid frequency modulation service in each scheduling period can be predicted by referring to the historical operation data of the power grid.
And S2, obtaining a heat demand side response plan of each scheduling time period on the operation day according to the electric energy marginal price.
The thermal demand side response plan may refer to a thermal demand side, such as a building, and its own response plan may be temperature, for example.
And S3, establishing a first profit model corresponding to the electric boiler system not participating in the power grid frequency modulation service and a second profit model corresponding to the electric boiler system participating in the power grid frequency modulation service.
In the embodiment of the invention, a corresponding profit model when the electric boiler system does not participate in power grid frequency modulation, namely, the electric boiler system only provides heat service for a heat demand side (only provides heat supply service and does not provide power grid frequency modulation service) is called as a first profit model, and a corresponding profit model when the electric boiler system participates in power grid frequency modulation service, namely, the electric boiler system not only provides heat service for the heat demand side but also provides frequency modulation service for a power grid (the electric boiler system also participates in point-on frequency modulation as demand side frequency modulation resource while providing heat supply service) is called as a second profit model, wherein the value of the profit model represents the profit of the electric boiler system.
Specifically, a first profit model and a second profit model can be established on the basis that the electric boiler system participates in a power grid demand side management mechanism and a supply and demand interaction mode based on thermal demand side response, wherein the profit, the electricity consumption cost, the operation cost and the like when the electric boiler system provides services can be considered when the models are established.
And S4, determining a final scheduling scheme corresponding to the maximum profit of the electric boiler system according to the electric energy marginal price, the frequency modulation service clearing price, the heat demand side response plan, the first profit model and the second profit model, wherein the final scheduling scheme comprises a maximum profit final value of the electric boiler system, a heat final value provided by the electric boiler system to the heat demand side in each scheduling period and an electric power final value provided for a power grid.
Specifically, determining a maximum profit initial value of the electric boiler system, a heat initial value provided by the electric boiler to a heat demand side and an electric power initial value provided to a power grid at each scheduling period according to the electric energy marginal price, the heat demand side response plan and a first profit model; and determining the maximum profit final value of the electric boiler system, the heat final value provided by the electric boiler to the heat demand side and the electric power final value provided by the electric grid in each scheduling period according to the heat initial value, the electric power initial value, the frequency modulation service clearing price, the heat demand side response plan and the second profit model.
And S5, scheduling the electric boiler system according to the final scheduling scheme.
Specifically, after the final scheduling scheme is obtained, the electric boiler system provides heat to the heat demand side according to the heat final value in the final scheduling scheme, and provides frequency modulation service for the power grid according to the electric power final value, and at the moment, the electric boiler system obtains the maximum benefit which is the maximum benefit final value.
Therefore, according to the optimal scheduling method for the electric boiler system to participate in the power grid frequency modulation service, the electric energy marginal price and the frequency modulation service clearing price are predicted, the heat demand side response plan is obtained according to the electric energy marginal price, two profit models of the electric boiler system are established, and then the electric boiler system is determined to participate in the power grid frequency modulation and provide heat service to the heat demand side when the profit is the maximum according to the electric energy marginal price, the frequency modulation service clearing price, the heat demand side response plan and the two profit models. Therefore, on the premise that the electric boiler system meets the heat load required by the heat demand side, the residual frequency modulation resources are participated in the management of the power grid demand side, the frequency modulation service is provided for the power grid, meanwhile, the benefit of the electric boiler system is maximized, the operation safety of the power grid is improved, and the overall benefit of the electric boiler system is improved.
In an embodiment of the present invention, the step S1 may include: acquiring historical data of a power auxiliary service market, wherein the historical data comprises first historical electric power of a power grid needing frequency modulation service and second historical electric power of the power grid actually providing the frequency modulation service; and predicting the electric energy marginal price purchased from the power grid by the electric boiler system in each scheduling period of the operating day and the frequency modulation service clearing price when the electric boiler system participates in the power grid frequency modulation service in each scheduling period of the operating day according to the acquired historical data.
Specifically, first, an electric boiler operator obtains a first historical electric power of a grid demand frequency modulation service and a second historical electric power (of other frequency modulation auxiliary systems) of the grid demand frequency modulation service from an electric power auxiliary service market, wherein the first historical electric power is a theoretical demand value, and the second historical electric power is an actual trading value. And then, predicting the electric energy marginal price of the electric boiler system for purchasing electricity from the power grid in each scheduling period of the operation day and the clearing price of the frequency modulation service when the electric boiler system participates in the frequency modulation service of the power grid by the electric boiler operator according to the acquired first historical electric power and the second historical electric power.
In an embodiment of the present invention, the step S2 may include: and according to the electric energy marginal price, an elastic compensation scheme of each scheduling time interval on the thermal demand side in the operating day is made and synchronized to the thermal demand side, so that the thermal demand side makes a thermal demand side response plan of each scheduling time interval in the operating day according to the elastic compensation scheme of each scheduling time interval.
The elastic compensation scheme refers to a compensation mode obtained when the heat demand side participates in power grid frequency modulation, and may be a direct compensation mode, that is, the more the heat demand side transfers heat load, the more economic compensation is provided, and may also be a discount preferential compensation mode, such as direct subsidy, energy consumption discount, and the like, which may be specifically determined according to actual demand.
Specifically, an electric boiler operator can make an elastic compensation scheme for a heat demand side in each scheduling period of an operating day according to the predicted electric energy marginal price and publish the elastic compensation scheme to the heat demand side, and then the heat demand side adjusts demand side response according to the elastic compensation scheme and in combination with self-required heat load and heat comfort demand, so as to make a heat demand side response plan of each scheduling period of the operating day and synchronize the heat demand side response plan to the electric boiler operator, so that the electric boiler operator obtains the heat demand side response plan.
In an embodiment of the present invention, the step S4 may include: determining the heat supply amount required by each heat user at the heat demand side in each scheduling period based on a heat demand side response plan, wherein the heat demand response plan comprises a heat demand response temperature; determining the response capacity of a heat demand side in each scheduling time period of a running day according to the heat supply amount required by each heat user in each scheduling time period, wherein the response capacity comprises an up-regulation response capacity and a down-regulation response capacity; inputting the electric energy marginal price into a first profit model, carrying out optimization solution on the first profit model by taking response capacity as a constraint condition and taking profit maximization as a target through a preset algorithm, and obtaining a maximum profit initial value of the electric boiler system, a heat initial value provided by the electric boiler system to a heat demand side at each scheduling period and an electric power initial value provided to a power grid, wherein the heat initial value is between the up-regulation response capacity and the down-regulation response capacity; inputting the clear price, the initial heat value and the initial electric power value of the frequency modulation service into a second profit model, optimizing the second profit model by using response capacity as a constraint condition and aiming at maximizing profit through a preset algorithm to obtain a maximum profit final value of the electric boiler system, a final heat value provided by the electric boiler system to a heat demand side in each scheduling period and a final electric power value provided to a power grid, wherein the final heat value is between the response capacity of up-regulation and the response capacity of down-regulation.
Further, determining the heat supply amount required by each heat user at the heat demand side in each scheduling period based on the heat demand side response plan may specifically include: acquiring external environment factor data and internal human factor data, wherein the external environment factor data comprises the current temperature, and the internal human factor data comprises the heat required by a hot user; determining the heat capacity of the building space to which each heat user belongs; in each scheduling period, determining a plurality of heats corresponding to the building space to which the heat consumer belongs according to external environmental factors and internal human factor data, wherein the plurality of heats comprise heat transferred by each wall surface, heat radiated by a window, heat transferred to indoor air by indoor thermal interference factors and indoor heat brought by indoor and outdoor air or adjacent air in an exchange manner; the amount of heat required by each thermal user at the thermal demand response temperature for each scheduled time period is determined based on the current temperature, the thermal capacity, and the plurality of heats.
The external environmental factor refers to an environmental factor at a heat demand side, such as the temperature of the day, and the internal human factor refers to a heat user factor, such as when the current user is not present, heat supply is not needed, and the heat supply is 0.
The prediction of the response capacity of the heat demand side is obtained based on a heat energy consumption process, the heat energy consumption process is a dynamic heat process of the building at a given heat comfort temperature, and the process can be represented by the following formula, namely the heat supply amount required by each heat user at each scheduling time interval at the heat demand response temperature can be calculated according to the following formula:
T a ＝T 1 -T 2 (2)
wherein, T 1 Is the thermal demand response temperature, T 2 Is the current temperature, T a Is the difference between the thermal demand response temperature and the current temperature, U is the wall number of the building to which the thermal user belongs, V is the heat capacity of the building space to which the thermal user belongs, Q ws,u,t Heat transferred for the u-th wall surface during the period t, Q win,t Heat radiated through the window for a period of t, Q con,t Heat transferred to the indoor air by the indoor thermal disturbance factor during the period of t, Q tra,t Heat brought in by indoor or outdoor air or air exchange in adjacent rooms during time t, Q offer,t The heat supply quantity required by the heat user in the time period t under the demand response plan.
Further, the thermal demand response temperature may include an optimum thermal comfort temperature Tbest, a maximum allowable thermal comfort temperature Tmax and a minimum allowable thermal comfort temperature Tmin, and the respective temperatures may be determined according to the types of thermal users, for example, a type a user minimum allowable thermal comfort temperature 22 ℃, a type b user minimum allowable thermal comfort temperature 20 ℃, and a type c user minimum allowable thermal comfort temperature 18 ℃.
In this example, the response capability of the heat demand side at each scheduling period on the operation day can be calculated and determined according to the following formula:
wherein G is the number of hot users, Q t,up For the up-regulation response capability of the heat demand side in the period t, Q t,down For turndown responsiveness of the heat demand side during time t, Q g,t,best The heat supply quantity required by the optimal heat comfortable temperature in the period t of the g-th heat user, Q g,t,Tmax The required heat supply at the maximum allowable thermal comfort temperature in the t period of the g-th thermal user, Q g,t,Tmin The minimum allowable heat comfort temperature is the heat supply amount required in the g-th heat user t period.
Specifically, an electric boiler operator collects external environmental factors and internal human factors to obtain current factors and the amount of heat required by each heat consumer, and then determines each heat usageThe heat capacity of the building space to which the user belongs, then, in every scheduling period, according to external environment factor and internal artificial factor, confirm a plurality of heats that the building space to which the user belongs corresponds, a plurality of heats include the heat of each wall transmission, the heat of radiation through the window, the heat and the indoor and outdoor air or the exchange of adjacent room air that indoor thermal disturbance factor transmitted indoor air bring indoor heat into, finally according to heat demand response temperature, current temperature, heat capacity and a plurality of heat, confirm the required heat supply volume of every scheduling period of every heat user under heat demand response temperature: obtaining the difference T between the thermal demand response temperature and the current temperature according to the formula (2) a Then, under the condition that t and the heat capacity V are known, the left value of the equal sign of the formula (1) can be calculated, namely, the total required heat quantity in the building space can be obtained, under the condition that a plurality of heat quantities on the right side of the equal sign of the formula (1) are known at t, the right value of the equal sign of the formula (1) can be obtained through any favorable prior art, and thus, the heat supply quantity Q required by the heat user in the period of t under the demand response plan can be obtained according to the formula (1) offer,t 。
Wherein. For each hot user, T in equations (1) and (2) can be set 1 Are respectively replaced by T best 、T max And T min Then, calculating according to a formula to obtain the heating load Q required by the optimal thermal comfort temperature at the time t of the g-th thermal user g,t,best The heating load Q required at the maximum allowable thermal comfort temperature in the g-th thermal user t period g,t,Tmax And the required heating load Q at the minimum allowable thermal comfort temperature of the g-th thermal user t period g,t,Tmin 。
Thereafter, the electric boiler operator can determine the response capacity Q of the heat demand side for up-regulation at each scheduling period of the operating day according to equation (3) t,up And downregulation of response Capacity Q t,down 。
After the up-regulation response capability and the down-regulation response capability are obtained, the electric boiler operator inputs the electric energy marginal price into a first profit model, and performs optimization solution on the first profit model through a preset algorithm (such as a genetic algorithm, an ant colony algorithm or a particle swarm algorithm) by taking the response capability as a constraint condition and aiming at profit maximization to obtain a maximum profit initial value of the electric boiler system, a heat initial value provided by the electric boiler system to a heat demand side in each scheduling period and an electric power initial value provided to a power grid.
And then inputting the frequency modulation service clearing price, the heat initial value and the electric power initial value into a second profit model, and optimizing the second profit model by using a preset algorithm (such as a genetic algorithm, an ant colony algorithm or a particle swarm algorithm) with response capacity as a constraint condition and with the goal of maximizing profit so as to obtain a maximum profit final value of the electric boiler system, a heat final value provided by the electric boiler system to a heat demand side at each scheduling period and an electric power final value provided by a power grid.
The frequency modulation service clearing price can comprise a time-interval frequency modulation capacity clearing price and a frequency modulation mileage clearing price.
In one example, the first revenue model is:
M 1 ＝I 2 -C 1 -C 2 -C 3
wherein, M 1 As a first revenue model, I 2 Heat supply benefit when providing heat service to heat demand side for electric boiler system, C 1 Cost of electricity purchase required to provide frequency modulation services to the grid and heat services to the heat demand side for an electric boiler system, C 2 For the heat storage cost, the heat storage cost is the sum of the heat dissipation cost and the heat transmission loss cost of the electric boiler system in the non-operation state, C 3 The cost of the heat supply network is the cost of the power consumption of the circulating water pump of the heat supply network in the operation of the electric boiler system.
The second revenue model is:
M 2 ＝I 1 +I 2 -C 1 -C 2 -C 3
wherein, M 2 As a second profit model, I 1 The method is used for the frequency modulation benefit when the electric boiler system participates in the power grid frequency modulation service.
Each benefit is illustrated separately as follows:
the frequency modulation benefit is:
I 1 ＝I cap +I mil
wherein H is total scheduling time interval of operation day, beta is frequency modulation performance index, sigma is frequency modulation mileage ratio, delta t is time step length, I cap For gain of frequency-modulated capacity, I mil For frequency-modulated mileage earnings, p cap,t Clearing price, p, for predicted t-time modulated capacity mil，t Clearing price, P, for predicted time-t-period frequency-modulated mileage offer,t Frequency modulation capacity provided for the t period.
In the fm gain, H may be 24 hours, where each 1 hour is a scheduling period, β, σ, Δ t may be determined according to specific needs, and p cap,t Clearing price, p, for the t-period FM capacity predicted in step S1 mil，t Calculating a clearing price, P, for the t-time period frequency-modulated mileage predicted in step S1 offer,t The frequency modulation capacity provided for the t period is a known value.
The heat supply benefit is as follows:
h is the total scheduling time interval of the operation day, G is the number of hot users, delta t is the time step length, and Q g,t,best The heat supply quantity required by the optimal heat comfortable temperature in the period t of the g-th heat user, Q g,t Amount of heat supplied to g users for period t, p heat For the unit price of heat supply, eta g And g is the t-period elastic compensation coefficient of the user.
In the heat supply income, Q g,t For optimization parameters requiring an optimization solution, p heat 、η g Is a known value.
The electricity purchasing cost is as follows:
where H is the total scheduling period of the day of operation, p grid,t For predicted marginal price of electric energy, p, of time t of day of operation eb,t And the delta t is the time step for the electric power exchanged between the electric boiler and the power grid in the period of t.
In the cost of purchasing electricity, p grid,t For p predicted in step S1 eb,t Optimization parameters of the solution need to be found.
The heat storage cost is as follows:
wherein H is the total scheduling time interval of the operation day, delta t is the time step, p heat Is a unit of heat power, Q sto,t Is the heat storage capacity of the heat storage device in the period t, mu s to,loss Is the heat loss rate of the heat storage device, mu sto,in For the charging efficiency of the heat storage device, mu sto,out For heat-releasing efficiency of the heat-storage device, Q sto,in,t And Q sto,out,t The heat storage device is charged and discharged with heat power in the t time period.
Various parameters of the thermal storage cost may be obtained from the thermal storage device.
The cost of the heat supply network is as follows:
wherein H is the total scheduling time interval of the operation day, delta t is the time step, and omega wp For the power consumption to heat transfer ratio of the water pump, p grid,t For predicted marginal price of electric energy, Q, for time period t of operation day wp,t The thermal power transmitted by the water pump in the period t.
Omega in heat net cost wp And Q wp,t Can be obtained according to actual conditions and is a known value.
Specifically, when performing optimization solution, as shown in fig. 4, the relevant parameters of the electric boiler system related to each benefit and each cost are obtained, the relevant parameters are input into the heat supply benefit and each cost function, the marginal price of electric energy is input into the electricity purchase cost, optimization iterative calculation is performed on the electric power exchanged between the electric boiler and the power grid in each period and the heat supplied to each user in each period according to the expression of the first benefit model by using a genetic algorithm, an ant colony algorithm or a particle swarm algorithm, wherein the heat is constrained by the up-regulation response capability and the down-regulation response capability, iterative calculation is performed with the maximum benefit target, and until the iteration is finished, the maximum benefit initial value of the electric boiler system, the heat initial value provided by the electric boiler system to the heat demand side in each scheduling period and the electric power initial value provided to the power grid are obtained, wherein the heat initial values are between the up-regulation response capability and the down-regulation response capability.
And then inputting the frequency modulation capacity clearing price and the frequency modulation mileage clearing price into a frequency modulation profit formula to obtain frequency modulation profit, and inputting the calculated initial heat value and the calculated initial electric power value into a second profit model to perform optimization iterative computation, wherein the heat is constrained by the response capacity of the upper adjustment and the response capacity of the lower adjustment, the maximum profit is used as a target to perform iterative computation by adopting a genetic algorithm, an ant colony algorithm or a particle swarm algorithm, and the maximum profit final value of the electric boiler system, the heat final value provided by the electric boiler system to the heat demand side at each scheduling period and the electric power final value provided to the power grid are obtained until the iteration is finished, wherein the heat final value is between the response capacity of the upper adjustment and the response capacity of the lower adjustment.
That is, after obtaining the maximum profit when the electric boiler system does not participate in the grid frequency modulation service, the initial heat value provided to the heat demand side and the initial electric power value provided to the grid according to the first profit model, adding the frequency modulation service clearing price on the basis of the result obtained according to the first profit model, inputting the frequency modulation service clearing price and the result obtained according to the first profit model into the second profit model, and performing iterative calculation of the optimization parameters once again to obtain the maximum profit end value of the electric boiler system, the final heat value provided to the heat demand side and the final electric power value provided to the grid by the electric boiler system at each scheduling period, thereby obtaining the optimal scheduling scheme for maximizing the electric boiler operator, i.e., the period-by-period output curve and the period-by-period heat supply curve of the electric boiler and the optimal operation profit.
It should be noted that the maximum profit initial value obtains the maximum profit when the electric boiler system only provides heat service, the maximum profit final value obtains the maximum profit when the electric boiler system also participates in the frequency modulation of the power grid while providing heat service, and the maximum profit final value can be larger than the maximum profit initial value, that is, the profit is higher when the electric boiler system participates in the frequency modulation of the power grid.
In summary, the method provided by the embodiment of the invention fully mobilizes the capability of the heat demand side to provide the grid frequency modulation service, improves the energy utilization efficiency to a certain extent, enables the electric boiler system to participate in the grid demand side management of the remaining frequency modulation resources on the premise of meeting the heat load required by the heat demand side, improves the operation safety of the grid, improves the overall benefit of the heating system, considers the grid demand side management, provides the grid with the frequency modulation auxiliary service through the electric boiler, improves the operation benefit, and improves the economy of the heating system.
The invention further provides an optimized scheduling device for the electric boiler system to participate in the power grid frequency modulation service, which corresponds to the optimized scheduling method for the electric boiler system to participate in the power grid frequency modulation service of the embodiment.
Fig. 5 is a block diagram illustrating an optimized scheduling apparatus for participating in grid frequency modulation service in an electric boiler system according to an embodiment of the present invention.
As shown in fig. 5, the optimized scheduling apparatus for participating in grid frequency modulation service of the electric boiler system includes a prediction module 10, a first determination module 20, an establishment module 30, a second determination module 40, and a scheduling module 50.
The prediction module 10 is configured to predict an electric energy marginal price at which the electric boiler system purchases electricity from the power grid at each scheduling period of an operating day, and a frequency modulation service clearing price at which the electric boiler system participates in a frequency modulation service of the power grid at each scheduling period of the operating day; the first determining module 20 is configured to obtain a thermal demand side response plan of each scheduling time period on the operation day according to the electric energy marginal price; the establishing module 30 is configured to establish a first profit model corresponding to the electric boiler system not participating in the grid frequency modulation service, and a second profit model corresponding to the electric boiler system participating in the grid frequency modulation service; the second determining module 40 is configured to determine a final scheduling scheme corresponding to the profit maximization of the electric boiler system according to the electric energy marginal price, the frequency modulation service clearing price, the thermal demand side response plan, the first profit model and the second profit model, where the final scheduling scheme includes a maximum profit end value of the electric boiler system, a heat end value provided by the electric boiler system to the thermal demand side at each scheduling period, and an electric power end value provided to the power grid; the scheduling module 50 is configured to schedule the electric boiler system according to the final scheduling scheme.
It should be noted that, for the specific implementation and implementation principle of the optimal scheduling device for participating in the grid frequency modulation service of the electric boiler system, reference may be made to the specific implementation of the optimal scheduling method for participating in the grid frequency modulation service of the electric boiler system, and details are not described here for avoiding redundancy.
The optimal scheduling device for the electric boiler system to participate in the power grid frequency modulation service enables the electric boiler system to participate in the power grid demand side management on the premise of meeting the heat load required by the heat demand side, provides the frequency modulation service for the power grid, and simultaneously enables the electric boiler system to have the maximum benefit, thereby improving the operation safety of the power grid and improving the overall benefit of the electric boiler system.
In the description of the present invention, 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 to imply that the number of technical features indicated is significant. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. The meaning of "plurality" is two or more 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. Moreover, various embodiments or examples and features of various embodiments or examples described in this specification can be combined and combined by one skilled in the art without being mutually inconsistent.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments. In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
Although embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are exemplary and not to be construed as limiting the present invention, and that changes, 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 (14)
1. An optimal scheduling method for an electric boiler system to participate in power grid frequency modulation service is disclosed, wherein the electric boiler system comprises an electric boiler and a heat storage device, and is characterized by comprising the following steps:
predicting the electric energy marginal price purchased by the electric network from the electric power during each scheduling period of the operating day and the clearing price of the frequency modulation service when the electric boiler system participates in the frequency modulation service of the electric network during each scheduling period of the operating day;
obtaining a thermal demand side response plan of each scheduling time period of the operation day according to the electric energy marginal price;
establishing a first profit model corresponding to the electric boiler system when not participating in the power grid frequency modulation service and a second profit model corresponding to the electric boiler system when participating in the power grid frequency modulation service;
determining a final scheduling scheme corresponding to the maximum profit of the electric boiler system according to the electric energy marginal price, the frequency modulation service clearing price, the heat demand side response plan, the first profit model and the second profit model, wherein the final scheduling scheme comprises a maximum profit final value of the electric boiler system, a heat final value provided by the electric boiler system to the heat demand side in each scheduling period and an electric power final value provided by an electric network;
and scheduling the electric boiler system according to the final scheduling scheme.
2. Method for the optimized dispatch of an electric boiler system for participation in grid frequency modulation services according to claim 1, the method for predicting the electric energy marginal price purchased by the electric power grid from the electric power grid in each scheduling period of the operating day and the clearing price of the frequency modulation service when the electric power grid frequency modulation service is participated in each scheduling period of the operating day comprises the following steps:
acquiring historical data of a power auxiliary service market, wherein the historical data comprises first historical electric power of a power grid requiring frequency modulation service and second historical electric power of the power grid actually providing the frequency modulation service;
and predicting the electric energy marginal price of the electric boiler system for purchasing electricity from the power grid in each scheduling period of the operation day and the clearing price of the frequency modulation service when the electric boiler system participates in the frequency modulation service of the power grid in each scheduling period of the operation day according to the acquired historical data.
3. The method for optimizing and scheduling participation of an electric boiler system in grid frequency modulation service according to claim 1, wherein obtaining a thermal demand side response plan for each scheduling period of the operation day according to the marginal price of electric energy comprises:
and according to the electric energy marginal price, an elastic compensation scheme of each scheduling time interval on the heat demand side in the operation day is made and is synchronized to the heat demand side, so that the heat demand side makes a heat demand side response plan of each scheduling time interval in the operation day according to the elastic compensation scheme of each scheduling time interval.
4. The method for optimally scheduling the participation of the electric boiler system in the grid frequency modulation service according to claim 1, wherein the step of determining a final scheduling scheme corresponding to the profit maximization of the electric boiler system according to the electric energy marginal price, the frequency modulation service clearing price, the thermal demand side response plan, the first profit model and the second profit model comprises the steps of:
determining the heat supply amount required by each heat user at the heat demand side in each scheduling period based on the heat demand side response plan, wherein the heat demand response plan comprises heat demand response temperature;
determining the response capacity of the heat demand side in each scheduling period of a running day according to the heat supply amount required by each heat user in each scheduling period, wherein the response capacity comprises an up-regulation response capacity and a down-regulation response capacity;
inputting the electric energy marginal price into the first profit model, and performing optimization solution on the first profit model by using a preset algorithm and taking the response capacity as a constraint condition and taking profit maximization as a target to obtain a maximum profit initial value of the electric boiler system, a heat initial value provided by the electric boiler system to a heat demand side at each scheduling period and an electric power initial value provided to a power grid, wherein the heat initial value is between the up-regulation response capacity and the down-regulation response capacity;
inputting the frequency modulation service clearing price, the heat initial value and the electric power initial value into the second profit model, optimizing the second profit model by using the response capacity as a constraint condition through a preset algorithm and aiming at maximizing profits to obtain a maximum profit final value of the electric boiler system, a heat final value provided by the electric boiler system to a heat demand side at each scheduling period and an electric power final value provided by a power grid, wherein the heat final value is between the up-regulation response capacity and the down-regulation response capacity.
5. The method for optimally scheduling the participation of an electric boiler system in grid frequency modulation service according to claim 4, wherein the step of determining the heat supply amount required by each heat user on the heat demand side in each scheduling period based on the heat demand side response plan comprises the following steps:
acquiring external environment factor data and internal human factor data, wherein the external environment factor data comprises the current temperature, and the internal human factor data comprises the heat required by a hot user;
determining the heat capacity of the building space to which each heat user belongs;
in each scheduling period, determining a plurality of heats corresponding to the building space to which the heat user belongs according to the external environmental factor and the internal human factor data, wherein the plurality of heats comprise heat transferred by each wall surface, heat radiated by a window, heat transferred to indoor air by an indoor thermal disturbance factor and indoor heat brought by indoor and outdoor air or adjacent room air in an exchange manner;
and determining the heat supply amount required by each heat user in each scheduling period at the heat demand response temperature according to the heat demand response temperature, the current temperature, the heat capacity and the plurality of heat quantities.
6. The method of claim 5, wherein the amount of heat required by each thermal user at the thermal demand response temperature for each scheduling period is calculated according to the following formula:
T a ＝T 1 -T 2
wherein, T 1 Is the thermal demand response temperature, T 2 Is said current temperature, T a Is the difference between the thermal demand response temperature and the current temperature, U is the number of building walls, V is the heat capacity of the building space to which the thermal user belongs, Q ws,u,t Heat transferred for the u-th wall surface during the period t, Q win,t Heat radiated through the window for a period of t, Q con,t Heat transferred to the indoor air by the indoor thermal disturbance factor during the period of t, Q tra,t Heat brought in by indoor or outdoor air or air exchange in adjacent rooms during time t, Q offer,t The heat supply quantity required by the heat user in the time period t under the demand response plan.
7. The method for optimizing scheduling participation of an electric boiler system in grid frequency modulation services according to claim 4, wherein the thermal demand response temperature comprises an optimal thermal comfort temperature, a maximum allowable thermal comfort temperature and a minimum allowable thermal comfort temperature, and the response capacity of the thermal demand side at each scheduling period of the operation day is calculated and determined according to the following formula:
wherein G is the number of hot users, Q t,up For the up-regulation response capability of the heat demand side in the period t, Q t,down For turndown responsiveness of the heat demand side during time t, Q g,t,best The heat supply quantity required by the optimal heat comfortable temperature in the period t of the g-th heat user, Q g,t,Tmax The required heat supply at the maximum allowable thermal comfort temperature in the t period of the g-th thermal user, Q g,t,Tmin The minimum allowable heat supply amount at the t period of the g-th heat user is the required heat supply amount at the temperature of the thermal comfort level.
8. The method of claim 4, wherein the first revenue model is:
M 1 ＝I 2 -C 1 -C 2 -C 3
wherein, M 1 As a first revenue model, I 2 Heat supply benefit when providing heat service to heat demand side for said electric boiler system, C 1 Cost of electricity purchase required to provide frequency modulation service to the grid and thermal service to the thermal demand side for said electric boiler system, C 2 For the heat storage cost, which is the sum of the heat dissipation cost and the heat delivery loss cost of the electric boiler system in the non-operating state, C 3 The cost of the heat supply network is the cost of the power consumption expense of the circulating water pump of the heat supply network in the operation of the electric boiler system;
the second yield model is:
M 2 ＝I 1 +I 2 -C 1 -C 2 -C 3
wherein, M 2 As a second profit model, I 1 And the frequency modulation benefit is generated when the electric boiler system participates in the power grid frequency modulation service.
9. The method for optimized scheduling of participation of an electric boiler system in grid frequency modulation services according to claim 8, wherein the frequency modulation benefit is:
I 1 ＝I cap +I mil
h is the total scheduling time interval of the operation day, beta is the frequency modulation performance index, sigma is the frequency modulation mileage ratio, delta t is the time step length, I cap For gain of frequency-modulated capacity, I mil For frequency-modulated mileage earnings, p cap,t For predicted tuned capacity clearing price, p, of time t mil，t For predicted t-time frequency-modulated mileage clearing price, P offer,t Frequency modulation capacity provided for the t period.
10. The method for optimally scheduling the participation of an electric boiler system in the grid frequency modulation service according to claim 8, wherein the heating profit is as follows:
wherein H is the total scheduling time interval of the operation day, G is the number of hot users, delta t is the time step length, Q g,t,best The heat supply quantity required by the optimal heat comfortable temperature in the period t of the g-th heat user, Q g,t The amount of heat supplied to the user for the period t,p heat for unit price of heat supply, eta g The t-period elastic compensation coefficient of the g users.
11. The method for optimizing and scheduling participation of an electric boiler system in grid frequency modulation service according to claim 8, wherein the electricity purchase cost is as follows:
where H is the total scheduling period of the day of operation, p grid,t For predicted marginal price of electric energy, p, of time t of day of operation eb,t And the delta t is the time step for the electric power exchanged between the electric boiler and the power grid in the period of t.
12. The method for optimizing and scheduling participation of an electric boiler system in grid frequency modulation service according to claim 8, wherein the heat storage cost is as follows:
wherein H is the total scheduling time interval of the operation day, delta t is the time step, p heat Is a heat power unit heat price, Q sto,t Is the heat storage capacity of the heat storage device in the period t, mu s to,loss Is the heat loss rate of the heat storage device, mu sto,in For the charging efficiency of the heat storage device, mu sto,out For heat-releasing efficiency of the heat-storage device, Q sto,in,t And Q sto,out,t The heat charging and discharging power of the heat storage device is t time.
13. The method for optimally scheduling the participation of an electric boiler system in grid frequency modulation service according to claim 8, wherein the heat supply network cost is as follows:
wherein H is the total scheduling time interval of the operation day, delta t is the time step, and omega wp For the power consumption to heat transfer ratio of the water pump, p grid,t For predicted marginal price of electric energy, Q, for time period t of operation day wp,t The thermal power transmitted by the water pump in the period t.
14. An optimized scheduling device for participating in power grid frequency modulation service of an electric boiler system, wherein the electric boiler system comprises an electric boiler and a heat storage device, and is characterized by comprising:
the prediction module is used for predicting the electric energy marginal price purchased from the power grid by the electric boiler system in each scheduling period of the operating day and the frequency modulation service clearing price when the electric boiler system participates in the frequency modulation service of the power grid in each scheduling period of the operating day;
the first determining module is used for obtaining a thermal demand side response plan of each scheduling time interval on the operating day according to the electric energy marginal price;
the establishing module is used for establishing a corresponding first profit model when the electric boiler system does not participate in the power grid frequency modulation service and a corresponding second profit model when the electric boiler system participates in the power grid frequency modulation service;
a second determining module, configured to determine a final scheduling scheme corresponding to the maximum profit of the electric boiler system according to the electric energy marginal price, the frequency modulation service clearing price, the thermal demand side response plan, the first profit model, and the second profit model, where the final scheduling scheme includes a maximum profit final value of the electric boiler system, a thermal final value provided by the electric boiler system to the thermal demand side at each scheduling period, and an electric power final value provided to an electric grid;
and the scheduling module is used for scheduling the electric boiler system according to the final scheduling scheme.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210742249.4A CN115222219A (en) | 2022-06-27 | 2022-06-27 | Optimal scheduling method and device for electric boiler system participating in power grid frequency modulation service |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210742249.4A CN115222219A (en) | 2022-06-27 | 2022-06-27 | Optimal scheduling method and device for electric boiler system participating in power grid frequency modulation service |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115222219A true CN115222219A (en) | 2022-10-21 |
Family
ID=83610017
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210742249.4A Pending CN115222219A (en) | 2022-06-27 | 2022-06-27 | Optimal scheduling method and device for electric boiler system participating in power grid frequency modulation service |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115222219A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180356105A1 (en) * | 2017-04-28 | 2018-12-13 | Southeast University | Modeling Method of Combined Heat and Power Optimal Dispatching Model |
| CN110728405A (en) * | 2019-10-12 | 2020-01-24 | 华北电力大学 | Day-ahead market trading method for heat storage electric boiler load participating in wind power consumption |
| CN113031447A (en) * | 2021-03-15 | 2021-06-25 | 上海电气集团股份有限公司 | Configuration method, system, equipment and medium for equipment in combined cooling heating and power system |
| CN114118609A (en) * | 2021-12-03 | 2022-03-01 | 国网辽宁省电力有限公司营口供电公司 | Comprehensive energy system optimization operation method considering energy market trading |
-
2022
- 2022-06-27 CN CN202210742249.4A patent/CN115222219A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180356105A1 (en) * | 2017-04-28 | 2018-12-13 | Southeast University | Modeling Method of Combined Heat and Power Optimal Dispatching Model |
| CN110728405A (en) * | 2019-10-12 | 2020-01-24 | 华北电力大学 | Day-ahead market trading method for heat storage electric boiler load participating in wind power consumption |
| CN113031447A (en) * | 2021-03-15 | 2021-06-25 | 上海电气集团股份有限公司 | Configuration method, system, equipment and medium for equipment in combined cooling heating and power system |
| CN114118609A (en) * | 2021-12-03 | 2022-03-01 | 国网辽宁省电力有限公司营口供电公司 | Comprehensive energy system optimization operation method considering energy market trading |
Non-Patent Citations (2)
| Title |
|---|
| 刘明华等: "电极式锅炉参与电网调频服务下供热系统日前优化调度", 电力建设, vol. 41, no. 01, 1 January 2020 (2020-01-01), pages 1 - 2 * |
| 刘明华等: "电极式锅炉参与电网调频服务下供热系统日前优化调度", 电力建设, vol. 41, no. 01, pages 1 - 2 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Tang et al. | A game theory-based decentralized control strategy for power demand management of building cluster using thermal mass and energy storage | |
| Wei et al. | A bi-level scheduling model for virtual power plants with aggregated thermostatically controlled loads and renewable energy | |
| Jin et al. | Foresee: A user-centric home energy management system for energy efficiency and demand response | |
| Gu et al. | Bi-level optimal low-carbon economic dispatch for an industrial park with consideration of multi-energy price incentives | |
| Pan et al. | Feasible region method based integrated heat and electricity dispatch considering building thermal inertia | |
| Adika et al. | Demand-side bidding strategy for residential energy management in a smart grid environment | |
| US10054971B2 (en) | Received energy reduction information calculation apparatus, received energy reduction information calculation method and program | |
| CN111008739B (en) | Optimal regulation and control and income distribution method and system for cogeneration virtual power plant | |
| CN108494012B (en) | Online optimization method for regional comprehensive energy system considering electricity-to-gas technology | |
| CN112036934A (en) | Quotation method for participation of load aggregators in demand response considering thermoelectric coordinated operation | |
| CN112529271B (en) | Optimized scheduling method for providing standby auxiliary service of power grid by controllable load cluster | |
| CN113746089A (en) | Multi-user-oriented multi-time-scale power package and family energy optimization method | |
| CN114462724B (en) | Park aggregator double-layer optimization scheduling method considering multi-energy price incentive comprehensive demand response model | |
| Yang et al. | Exploring blockchain for the coordination of distributed energy resources | |
| CN112116150A (en) | Method for regulating heat accumulating type electric heating power market by load aggregators | |
| Kou et al. | A distributed energy management approach for residential demand response | |
| CN109800927B (en) | Distributed optimization method for power distribution network in bilateral power market environment | |
| CN114970962A (en) | Optimization method of electric and thermal comprehensive energy system | |
| CN111553544A (en) | Industrial park distributed comprehensive demand response method based on consistency algorithm | |
| Lu et al. | Two-stage robust scheduling and real-time load control of community microgrid with multiple uncertainties | |
| CN110555562B (en) | Layered energy management method for comprehensive energy system in ubiquitous power Internet of things | |
| CN109713729B (en) | Temperature control cost optimization algorithm of energy management system in micro-grid | |
| CN111523697A (en) | Comprehensive energy service cost allocation and pricing calculation method | |
| CN115222219A (en) | Optimal scheduling method and device for electric boiler system participating in power grid frequency modulation service | |
| CN116432807A (en) | Comprehensive demand response system and method considering coupling effect and uncertainty |
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 |