A low-carbon flexible control method and system for power distribution in rainwater storage tanks

Abstract

The present invention provides a low-carbon flexible control method and system for rainwater storage tank power distribution, including: obtaining meteorological data, storage tank usage data and historical photovoltaic output data of the area where the rainwater storage tank is located, and predicting the photovoltaic output curve during the interval between the end of this rainfall and the beginning of water filling of the storage tank at the next rainfall according to the obtained data, and obtaining the remaining energy storage capacity when the storage tank begins to be emptied at the end of this rainfall; taking the shortest emptying time Δt as the basis for the prediction of the photovoltaic output curve during the interval between the end of this rainfall and the beginning of water filling of the storage tank at the next rainfall; and taking the shortest emptying time Δt as the basis for the prediction of the photovoltaic output curve during the interval between the end of this rainfall and the beginning of water filling of the storage tank at the next rainfall. s As the goal, the flexible control strategy M1 of the emptying pump for emptying the rainwater storage tank is optimized and designed only when photovoltaic and energy storage are used; it is determined whether there is a solution for the control strategy M1, and when there is a solution, the control strategy M1 is executed according to the pipeline dispatching instruction to realize the low-carbon flexible control of the power distribution of the rainwater storage tank. The present invention combines the power consumption characteristics of the rainwater storage tank, proposes a solution to the problem of flexible control optimization of its power distribution system, and provides an effective control method and system for the low-carbon operation of the rainwater storage tank.

Description

Technical Field

[0001] The present invention relates to the field of power distribution system control for rainwater storage tanks, and in particular to a low-carbon flexible control method and system for power distribution for rainwater storage tanks. Background Art

[0002] In the rapid process of urbanization, the stability and safety of urban operations have become an important link that cannot be ignored in urban construction and planning. As a facility specifically used to regulate and store urban rainwater, rainwater storage tanks play a significant role in solving the runoff pollution problem caused by rainwater and controlling the total amount and peak value of runoff, effectively reducing the risk of urban waterlogging.

[0003] There are four operating modes for rainwater storage tanks: drought mode, inflow mode, full pool mode, and emptying mode. In drought mode, the storage tank is empty; when it rains, the storage tank enters inflow mode, at which time the initial rainwater with a high pollution concentration will flow into the storage tank; when the storage tank reaches full load, it enters full pool mode, at which time the excess rainwater will flow into the water body through the overflow facility; after the weather clears, the storage tank enters emptying mode, at which time the emptying pump will be used to discharge the rainwater in the storage tank. It is worth noting that the energy consumption of rainwater storage tanks is mainly concentrated in the emptying mode. At present, many rainwater storage tanks directly use municipal electricity to provide energy, and their power consumption cannot be ignored, which has huge potential for energy conservation and emission reduction.

[0004] According to the operating principle of the rainwater storage tank, when the rainfall stops and the weather turns sunny, the storage tank will enter the emptying mode. At this time, the weather conditions are usually conducive to the power generation of renewable energy, and there is a large overlap between the two. In summer, there is more rain, resulting in a larger power consumption of the storage tank; sufficient sunlight, the power generation of renewable energy increases accordingly; while in winter, there is less rain, the power consumption of the storage tank decreases accordingly, the sunlight is weak, and the power generation of renewable energy decreases. For the rainwater storage tank, its main power load comes from the emptying pump. Therefore, how to control the operation of the rainwater storage tank emptying pump so that it can take into account the pipeline dispatching instructions and the changing weather conditions while emptying to achieve the requirements of flow control and peak reduction is an important problem faced by the realization of low-carbon operation control of the rainwater storage tank. Summary of the invention

[0005] In view of the defects in the prior art, the object of the present invention is to provide a low-carbon flexible control method and system for electricity distribution in rainwater storage tanks.

[0006] According to one aspect of the present invention, a low-carbon flexible control method for power distribution in a rainwater storage tank is provided, comprising:

[0007] S1, obtain the meteorological data, storage pool usage data and historical photovoltaic output data of the area where the rainwater storage pool is located, and based on the obtained data, predict the photovoltaic output curve from the end of this rainfall to the beginning of the storage pool being emptied to the beginning of the next rainfall, and at the same time obtain the remaining energy storage capacity when the storage pool begins to be emptied after this rainfall;

[0008] S2, based on the photovoltaic output curve and the remaining energy storage capacity, with the shortest discharge time Δt s As the goal, the optimization design is limited to the use of photovoltaic and energy storage, and the flexible control strategy M1 of the emptying pump for emptying the air storage tank rainwater;

[0009] S3, determining whether there is a solution for the control strategy M1. If there is a solution, executing the control strategy M1 according to the pipe network dispatching instruction to achieve low-carbon flexible control of power distribution in the rainwater storage tank.

[0010] Preferably, the S1 includes:

[0011] Obtain meteorological data, historical usage data of the regulating reservoir, and historical photovoltaic output data. The meteorological data include: historical precipitation, solar radiation intensity, and temperature data of the area where the regulating reservoir is located; current precipitation, solar radiation intensity, and temperature data; and future precipitation, solar radiation intensity, and temperature forecast data obtained from the local meteorological station;

[0012] According to the meteorological data and historical usage data of the regulating reservoir, it is predicted that the interval time Δt between the end of this rainfall and the beginning of the emptying of the regulating reservoir and the beginning of the filling of the regulating reservoir at the next rainfall is INR ;

[0013] According to the meteorological data and historical photovoltaic output data, it is predicted that the interval time Δt from the end of this rainfall to the beginning of the emptying of the regulating reservoir to the beginning of the filling of the regulating reservoir at the next rainfall is INR The internal photovoltaic output curve; at the same time, the state of charge (SOC) of the energy storage when the rainfall ends and the storage tank begins to be emptied 1 .

[0014] Preferably, the S2 comprises:

[0015] Get the amount of rainwater Q that needs to be discharged from the storage tank at this time;

[0016] Design an objective function with the shortest emptying time as the goal, specifically:

[0017] Δt s =min(s×Δt f )

[0018] Among them, 0≤s≤k, k is the value of Δt INR The number of time periods divided according to actual demand, s is the number of empty time periods, Δt sis the shortest emptying time, Δt f Δt INR The length of the time period divided by actual demand, assuming that each variable is in Δt f The inside remains unchanged;

[0019] Designing constraints of the objective function;

[0020] The flexible control strategy M1 of the draining pump for draining the air storage tank within the shortest draining time is calculated according to the objective function and the constraint conditions.

[0021] Preferably, the constraints include energy constraints, energy storage constraints, venting pump efficiency constraints, and flow constraints;

[0022] Wherein, the energy constraint is:

[0023] The total energy consumed by the emptying pump of the storage tank in the i-th time period is less than or equal to the consumable energy in the time period: is the power of the jth venting pump in the i-th time period, n is the number of venting pumps, W i W is the total energy consumed by the venting pump in the i-th time period; ei is the energy that can be consumed in the i-th time period. The energy that can be consumed in the i-th time period is the sum of the dischargeable energy of photovoltaic and energy storage in this time period: W ei =Δt f ×(P PVi +P ESSi ),i=1,2,…k, where P PVi is the average value of the predicted photovoltaic output curve in the i-th time period, P ESSi is the average discharge power of the energy storage in the i-th time period;

[0024] Wherein, the energy storage constraint is:

[0025] The energy storage charging and discharging in the i-th time period is subject to power and charge state constraints

[0026]

[0027] Among them, SOC i+1 =g 1 (SOC i ,P ESSi ), SOC i is the energy storage charge state in the i-th time period, g 1 Indicates the SOC in the i+1th time period i+1 and SOC in the i-th time period i and discharge power P ESSi There is a functional relationship between them. The specific functional relationship needs to be determined according to the actual energy storage type and conditions. ESS_maxis the maximum discharge power of the energy storage battery, SOC min is the minimum value of the energy storage state of charge, SOC max is the maximum value of the energy storage charge state;

[0028] Wherein, the vent pump efficiency constraint is:

[0029]

[0030] Adjust frequency f ij To achieve the venting pump power P ij Flexible adjustment, where f ij is the frequency of the jth venting pump in the i-th time period, H ij is the j-th vent pump head in the i-th time period, Q ij is the discharge flow rate of the jth discharge pump in the i-th time period, L i The liquid level of the storage tank in the i-th time period, η ij is the operating efficiency of the jth venting pump in the i-th time period, η min is the lower limit of the vent pump operating efficiency, η max It is the upper limit of the operating efficiency of the vent pump;

[0031] g 2 Indicates the vent pump power P ij With its f ij , Q ij , H ij , η ij There is a functional relationship between g 3 Indicates the vent pump head H ij With L i , Q ij There is a functional relationship between g 4 Indicates the i+1th time period L i+1 and the i-th time period L i And the venting flow rate Q of the venting pump ij There is a functional relationship between g 2 , g 3 , g 4 The specific functional relationship needs to be determined according to the actual equipment type and working conditions;

[0032] The flow constraint is:

[0033]

[0034] At the same time, when i = s, When i=s+1,s+2,…k,

[0035] If there is any consumable energy left in any time period, it will be fed to the mains;

[0036] Among them, the consumable energy in the i-th time period is

[0037] W ei =Δt f ×(P PVi +P ESSi ),i=1,2,…k

[0038] The remaining consumable energy in the i-th time period

[0039]

[0040] When W s >0, then W s Feed to mains electricity.

[0041] Preferably, the S3 includes:

[0042] S301, obtaining the pipe network dispatching instruction for discharging the air storage tank for a time Δt o , when the control strategy M1 has a solution, let Δt=min[Δt o ,Δt s ] and when Δt=Δt s When , M1 starts to execute;

[0043] S302, obtaining the weather data at this time, the amount of rainwater Q that needs to be discharged from the storage tank, and the interval time Δt from the time when the control strategy predicts that the discharge will be completed fcst , predict the interval time Δt from now to the next rainfall when the storage tank starts to fill with water INR , if Δt INR ≥Δt fcst Then go to S303;

[0044] S303, determine whether the emptying of the storage tank is completed. If not, wait for Δt W After the time has passed, go to S302; upon completion, update the historical precipitation, solar radiation intensity, temperature, photovoltaic output data and historical usage data of the storage tank, and end the emptying process of the rainwater storage tank.

[0045] Preferably, in S3, if the control strategy M1 has no solution or has a solution but the emptying time requirement of the pipeline scheduling instruction is less than the shortest emptying time Δt of M1 s When the venting pump flexible control strategy M2 is further selected for execution, wherein the venting pump flexible control strategy M2 is based on the photovoltaic output curve and the remaining amount of energy storage, with the goal of minimizing operating costs, and optimizing the design to allow the use of photovoltaic, energy storage and city power, and determines the venting pump flexible control strategy for the venting storage tank;

[0046] During the execution of the control strategies M1 and M2, the real-time weather conditions are used to determine whether to continue to execute the control strategy itself or to re-optimize the design of the control strategy M2 and cyclically consider the real-time weather conditions to complete the execution, thereby realizing low-carbon flexible control of power distribution in the regulating reservoir.

[0047] Preferably, the S3 includes:

[0048] S31, obtain the pipe network dispatching instruction for the time Δt of discharging the air storage tank o If there is no solution for the control strategy M1, take Δt=min[Δt INR ,Δt o ] Go to S32; if the control strategy M1 has a solution, take Δt=min[Δt o ,Δt s ], if Δt≠Δt s , then go to S32, if Δt=Δt s , then start executing M1 and go to S33;

[0049] S32, design the objective function and its constraints with the lowest operating cost as the goal:

[0050]

[0051] Among them, c m For the lowest operating cost, c mi is the city electricity price in the i-th time period, r is the number of time periods into which Δt is divided according to actual demand;

[0052] According to the objective function and the constraint conditions, a flexible control strategy M2 for the drain pump for draining rainwater from the air storage tank at the lowest operating cost is obtained, and M2 is started to be executed;

[0053] S33, obtaining the weather data at this time, the amount of rainwater Q that needs to be discharged from the storage tank, and the interval time Δt from the time when the control strategy predicts that the discharge will be completed fcst , predict the interval time Δt from now to the next rainfall when the storage tank starts to fill with water INR , if Δt INR <Δt fcst , then Δt=Δt INR Re-predict the photovoltaic output curve within Δt, and obtain the state of charge of the energy storage at this time, which is recorded as SOC 1 Go to S32; if Δt INR ≥Δt fcst Then go to S34;

[0054] S34, determine whether the rainwater storage tank is emptied this time, if not, wait for Δt WAfter the time has passed, go to S33; upon completion, update the historical precipitation, solar radiation intensity, temperature, photovoltaic output data and historical usage data of the storage tank, and end the process of emptying the rainwater storage tank.

[0055] Preferably, the constraints include energy constraints, energy storage constraints, venting pump efficiency constraints, and flow constraints;

[0056] Wherein, the energy constraint is:

[0057]

[0058] W ei =Δt f ×(P PVi +P ESSi ),i=1,2,…r

[0059] Wherein, the energy storage constraint is:

[0060]

[0061] Among them, SOC i+1 =g 1 (SOC i ,P ESSi )

[0062] Wherein, the vent pump efficiency constraint is:

[0063]

[0064] The flow constraint is:

[0065]

[0066] According to a second aspect of the present invention, a low-carbon flexible control system for power distribution in a rainwater storage tank is provided, comprising:

[0067] Data acquisition module, which obtains meteorological data of the area where the rainwater storage tank is located, storage tank usage data and historical photovoltaic output data, and pipe network dispatching instructions. Based on the acquired data, it predicts the photovoltaic output curve from the end of this rainfall to the beginning of the storage tank being emptied to the beginning of the next rainfall or from this time to the beginning of the next rainfall, and obtains the remaining energy storage capacity;

[0068] An optimization control module, based on the photovoltaic output curve and the remaining energy storage capacity, with the shortest emptying time as the goal, optimizes the design of a flexible control strategy M1 for the emptying pump for emptying the rainwater in the air storage tank when photovoltaic and energy storage are used only;

[0069] A decision-making execution module determines whether there is a solution to the control strategy M1. When a solution exists, the control strategy M1 is executed according to the pipeline network dispatching instruction to achieve low-carbon flexible control of the power distribution of the rainwater storage tank.

[0070] Compared with the prior art, the embodiments of the present invention have at least one of the following beneficial effects:

[0071] The low-carbon flexible control method and system for power distribution in a rainwater storage tank provided in the embodiments of the present invention, combined with the power consumption characteristics of the rainwater storage tank itself, proposes a solution to the problem of flexible control optimization of the power distribution system in a rainwater storage tank, and provides an effective control strategy for implementing low-carbon operation of the rainwater storage tank.

[0072] The low-carbon flexible control method and system for rainwater storage tank power distribution provided by the embodiment of the present invention reduces carbon emissions by comprehensively considering the energy supply of photovoltaic and energy storage to the rainwater storage tank, and introduces mains power supply when necessary, thereby achieving the goal of low-carbon energy saving. The method and system improve energy utilization efficiency by optimizing energy configuration, thereby reducing energy consumption and carbon emissions.

[0073] The low-carbon flexible control method and system for power distribution in a rainwater storage tank provided in the embodiments of the present invention collects historical and real-time data on weather and the storage tank, and predicts the photovoltaic output and the usage interval of the storage tank, thereby greatly improving the effect of controlling the flow rate of the rainwater storage tank to reduce the peak value.

[0074] The low-carbon flexible control method and system for power distribution in rainwater storage tanks provided in the embodiments of the present invention have the ability to flexibly respond to different types of discharge requirements and can formulate optimal control strategies, such as optimizing control according to pipeline scheduling instructions and real-time weather discharge requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0076] Figure 1 It is a flow chart of a low-carbon flexible control method for electricity allocation to a rainwater storage tank in one embodiment of the present invention;

[0077] Figure 2 It is a schematic diagram of the structure of the power distribution system of the rainwater storage tank in a preferred embodiment of the present invention;

[0078] Figure 3 It is a flow chart of various steps of a low-carbon flexible control method for electricity allocation to a rainwater storage tank in a preferred embodiment of the present invention;

[0079] Figure 4 This is a framework diagram of a low-carbon flexible control system for power distribution to a rainwater storage tank in one embodiment of the present invention. DETAILED DESCRIPTION

[0080] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several variations and improvements may be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0081] The present invention provides an embodiment, a low-carbon flexible control method for rainwater storage tank power supply, which can be found in Figure 1 The specific process includes:

[0082] S1, obtain the meteorological data, storage pool usage data and historical photovoltaic output data of the area where the rainwater storage pool is located, and based on the obtained data, predict the photovoltaic output curve from the end of this rainfall to the beginning of the storage pool being emptied to the beginning of the next rainfall, and at the same time obtain the remaining energy storage capacity when the storage pool begins to be emptied after this rainfall;

[0083] The above photovoltaic output data refers to the power of the electrical energy generated by the photovoltaic system under the condition of light. PVi The calculation formula is:

[0084] P PVi =η PV A PV M pi (1-k p (T i -T test ))

[0085] Among them, A PV is the photovoltaic installation area, η PV is the photovoltaic power generation efficiency at the reference temperature, M pi is the solar radiation intensity data obtained for the i-th time period, T i is the temperature data obtained for the i-th time period, T test is the reference temperature under standard test conditions, k p is the temperature coefficient of photovoltaics. At the same time, photovoltaic output will be limited by the rated power of photovoltaic modules. In summary, it can be seen that photovoltaic output is related to solar radiation intensity and temperature. Other influencing factors such as the installation position and angle of photovoltaic modules and the use time of photovoltaic modules, etc., which affect the conversion efficiency, and other photovoltaic module system information will be included in the historical photovoltaic output data.

[0086] S2, based on the photovoltaic output curve and the remaining energy storage capacity, with the shortest discharge time Δt sAs the goal, the optimization design is limited to the use of photovoltaic and energy storage, and the flexible control strategy M1 of the emptying pump for emptying the air storage tank rainwater;

[0087] S3, determining whether there is a solution for the control strategy M1. If there is a solution, executing the control strategy M1 according to the pipe network dispatching instruction to achieve low-carbon flexible control of power distribution in the rainwater storage tank.

[0088] This embodiment combines the power consumption characteristics of the rainwater storage tank itself, proposes a solution to the problem of flexible control optimization of the power distribution system of the rainwater storage tank, and provides an effective control strategy reference for implementing low-carbon operation of the rainwater storage tank.

[0089] In a preferred embodiment of the present invention, a preferred rainwater storage tank power distribution system is provided, see Figure 2 The rainwater storage tank power distribution system is a system formed by a DC-coupled photovoltaic unit, an energy storage unit, a grid access unit, a rainwater storage tank drain pump and a meteorological instrument, in which the control unit collects information and issues control strategies. Specifically,

[0090] The photovoltaic unit includes a single crystal 555Wp photovoltaic module, which is 11 in series and 5 in parallel, with a photovoltaic capacity of 30.525kWp. The open circuit voltage of the photovoltaic modules in series is 549.45V, and the photovoltaic DC / DC power is 30kW.

[0091] The energy storage unit capacity is 50kW / 110.592kWh, the energy storage DC / DC power is 50kW, and the energy storage battery operating voltage range is 403V~511.2V;

[0092] The grid access unit includes an AC / DC module: 50kW power, bidirectional operation, on-grid and off-grid switching control function, and a DC voltage adjustment range of 600-750V;

[0093] The DC / AC module connected to the rainwater storage tank discharge pump has a rated power of 18.5kW and a DC input range of 540-750V.

[0094] In a preferred embodiment of the present invention, a preferred process for implementing S1 is provided, which can be found in Figure 3 , the specific steps are as follows:

[0095] S11, obtain the historical precipitation, solar radiation intensity, temperature data and historical photovoltaic output data of the area where the rainwater storage tank is located; at the same time, use the meteorological instrument to collect the precipitation, solar radiation intensity and temperature data at this time; obtain the future precipitation, solar radiation intensity and temperature forecast data from the local meteorological station. Obtain the historical usage times of the storage tank;

[0096] S12, based on meteorological data statistics (historical, current and predicted precipitation data of the meteorological station) and storage pool data (historical usage frequency of the storage pool), predict the interval time Δt from the end of the current rainfall in the storage pool to the beginning of water filling in the storage pool at the next rainfall INR ;

[0097] The emptying and filling of the rainwater storage tank are closely related to the precipitation data. When the rainfall starts and the rainfall reaches a certain amount, the storage tank starts to fill with water, and when the rainfall ends, the storage tank starts to empty. Here, the meteorological data and the historical data of the storage tank are used as input to establish a recurrent neural network (RNN) model to predict the usage data of the storage tank in the future, and then obtain the interval time Δt from the end of this rainfall to the beginning of the emptying of the storage tank to the beginning of the filling of the storage tank at the next rainfall. INR .

[0098] S13, based on meteorological data statistics (historical solar radiation intensity and temperature data; current solar radiation intensity and temperature data; solar radiation intensity and temperature data predicted by the meteorological station) and historical photovoltaic output data, predict the interval time Δt from the end of this rainfall to the beginning of water filling in the regulating reservoir at the next rainfall. INR Internal photovoltaic output curve;

[0099] It is known that photovoltaic output is related to solar radiation intensity and temperature, so here we use meteorological data and historical photovoltaic output data as input to establish a long short-term memory network (LSTM) model to predict the interval time Δt from the end of this rainfall to the beginning of water filling in the next rainfall. INR Internal photovoltaic output curve.

[0100] At the same time, the energy storage charge state SOC when the storage tank starts to be emptied after the rainfall ends is obtained 1 (The SOC of a storage battery is the percentage of the battery's remaining power to its rated capacity).

[0101] The above embodiments can provide sufficient and accurate basis for subsequent strategy design.

[0102] The above embodiment collects historical and real-time data of weather and storage tanks to predict the use interval of photovoltaic output and storage tanks, thereby greatly improving the effect of controlling flow and reducing peak values ​​in rainwater storage tanks.

[0103] In a preferred embodiment of the present invention, a preferred process for implementing S2 is provided, which can be found in Figure 3 , the specific steps are as follows:

[0104] S21, obtain the amount of rainwater Q that needs to be discharged from the rainwater storage tank at this time

[0105] S22, optimize the design of the flexible control strategy M1 for the emptying pump to discharge rainwater from the air-conditioning storage tank in the fastest time when only photovoltaic and energy storage are used. The objective function with the shortest emptying time as the goal is:

[0106] Δt s =min(s×Δt f )

[0107] This objective function takes into account the situation where the venting pump is not running continuously at night or in other situations. INR The number of time periods divided according to actual demand, s is the number of empty time periods, Δt s is the shortest emptying time, Δt f Δt INR The length of the time period divided by actual demand, assuming that each variable is in Δt f The inside remains unchanged;

[0108] Furthermore, the better optimization constraints are:

[0109] (1) Energy constraints:

[0110] The total energy consumption of the storage tank emptying pump in the i-th time period W i Less than or equal to the consumable energy W in this time period ei , n is the number of venting pumps:

[0111]

[0112] Consumable energy W in the i-th time period ei is the sum of the dischargeable energy of photovoltaic and energy storage in this period, P PVi is the average value of the predicted photovoltaic output curve in the i-th time period, P ESSi is the average discharge power of the energy storage in the i-th time period:

[0113] W ei =Δt f ×(P PVi +P ESSi ),i=1,2,…k

[0114] (2) Energy storage constraints: The energy storage charging and discharging in the i-th time period is subject to power and charge state constraints

[0115]

[0116] in η ESS is the energy storage charging and discharging efficiency, E ESS is the rated capacity of energy storage, SOC i is the energy storage charge state in the i-th time period, PESS_max is the maximum discharge power of the energy storage battery, SOC min is the minimum value of the energy storage state of charge, SOC max is the maximum value of the energy storage charge state. Of course, g 1 The specific functional relationship is determined according to the actual energy storage type and conditions. In other embodiments, other forms of functions may be used, and this is not a sole limitation.

[0117] (3) Vent pump efficiency constraints:

[0118] The power P of the jth venting pump in the i-th time period ij With vent pump head H ij 、Flow Q ij , frequency f ij , efficiency η ij The numerical relationship can be obtained by fitting the numerical curve of the corresponding vent pump. For example, the characteristic curve of the vent pump model XFP351M-CH3 can be obtained by looking up its data sheet, where the vent pump frequency adjustment can be divided into five levels: 30Hz, 35Hz, 40Hz, 45Hz, and 50Hz. By taking points for fitting, the P curve at different frequencies can be obtained. ij With vent pump head H ij 、Flow Q ij , efficiency η ij Of course, the specific functional relationship needs to be determined according to the actual equipment type and working conditions. In other embodiments, other numerical relationship formulas can be used, and are not limited to the only one.

[0119] In order to keep the vent pump running efficiently, the vent pump efficiency is limited to [η min ,η max ]

[0120] η mini ≤η ij ≤η maxi ,i=1,2,…k,j=1,2…n

[0121] η ij is the operating efficiency of the vent pump j, η min is the lower limit of the vent pump operating efficiency, η max It is the upper limit of the operating efficiency of the vent pump;

[0122] At the same time, the vent pump head H ij The maximum height L that the liquid level in the regulating tank can change H At this time, the liquid level L i and pipe head loss H s There is a numerical relationship:

[0123]

[0124] in , the pipeline head loss is related to the venting pump flow rate Q ij , s is the resistance coefficient of the pipeline.

[0125] Liquid level L in the i+1th time period i+1 and the liquid level L in the i-th time period i and vent pump flow Q ij There is a numerical relationship:

[0126]

[0127] Where A is the bottom area of ​​the storage tank,

[0128] (4) Traffic Constraints:

[0129]

[0130] At the same time, when i = s, When i=s+1,s+2,…k,

[0131] According to the objective function and constraint conditions, the flexible control strategy M1 for the emptying pump of the air-conditioning storage tank in the shortest emptying time can be obtained.

[0132] Preferably, if there is any remaining energy in any time period, it is fed to the mains.

[0133] W ei =Δt f ×(P PVi +P ESSi ),i=1,2,…k

[0134] The remaining consumable energy in the i-th time period

[0135]

[0136] When W s >0, then W s Feed to mains electricity.

[0137] In a preferred embodiment of the present invention, a preferred process for implementing S3 is provided, which can be found in Figure 3 , the specific steps are as follows:

[0138] S301, obtaining the pipe network dispatching instruction for discharging the air storage tank for a time Δt o , when the control strategy M1 has a solution, let Δt=min[Δt o ,Δt s ] and when Δt=Δt sWhen , M1 starts to execute;

[0139] S302, obtaining the weather data at this time, the amount of rainwater Q that needs to be discharged from the storage tank, and the interval time Δt from the time when the control strategy predicts that the discharge will be completed fcst , predict the interval time Δt from now to the next rainfall when the storage tank starts to fill with water INR , if Δt INR ≥Δt fcst Then go to S303;

[0140] S303, determine whether the emptying of the storage tank is completed. If not, wait for Δt W After the time has passed, go to S302; upon completion, update the historical precipitation, solar radiation intensity, temperature, photovoltaic output data and historical usage data of the storage tank, and end the emptying process of the rainwater storage tank.

[0141] In a preferred embodiment of the present invention, another implementation of S3 is provided. In S3, if the control strategy M1 has no solution or has a solution but the emptying time requirement of the pipe network dispatching instruction is less than the shortest emptying time of M1, the emptying pump flexible control strategy M2 is further selected to be executed, wherein the emptying pump flexible control strategy M2 is based on the photovoltaic output curve and the remaining power of the energy storage, with the goal of minimizing operating costs, and optimizes the design to allow the use of photovoltaic, energy storage and city power, and determines the emptying pump flexible control strategy for emptying the rainwater storage tank;

[0142] During the execution of the control strategies M1 and M2, the real-time weather conditions are used to determine whether to continue to execute the control strategy itself or to re-optimize the design of the control strategy M2 and cyclically consider the real-time weather conditions to complete the execution, thereby realizing low-carbon flexible control of the power distribution of the rainwater storage tank.

[0143] In a preferred embodiment, an implementation process of S3 is further provided, specifically:

[0144] S31, obtain the time Δt required by the pipe network dispatch to discharge the air storage tank o If there is no solution for the control strategy M1, take Δt=min[Δt INR ,Δt o ] Go to S32; if the control strategy M1 has a solution, take Δt=min[Δt o ,Δt s ], if Δt≠Δt s , then go to S32, if Δt=Δt s , then start executing M1 and go to S33;

[0145] S32: Optimize the design of a flexible control strategy for the emptying pump to discharge rainwater from the air storage tank with the lowest operating cost when using photovoltaic, energy storage and city electricity. The objective function with the lowest operating cost as the goal is:

[0146]

[0147] where c m For the lowest operating cost, c mi is the electricity price in the i-th time period, and r is the number of time periods into which Δt is divided according to actual demand. The optimization constraints are:

[0148] (1) Energy constraints:

[0149]

[0150] W ei =Δt f ×(P PVi +P ESSi ),i=1,2,…k

[0151] (2) Energy storage constraints:

[0152]

[0153] SOC i is the energy storage charge state in the i-th time period, η ESS is the energy storage charging and discharging efficiency, P ESS_max is the maximum discharge power of the energy storage battery, SOC min is the minimum value of the energy storage state of charge, SOC max is the maximum value of the energy storage charge state;

[0154] (3) Vent pump efficiency constraints:

[0155] Similarly, the power P of the jth venting pump in the i-th time period is ij With vent pump head H ij 、Flow Q ij , frequency f ij , efficiency η ij The numerical relationship can be obtained by fitting the numerical curve of the vent pump of the corresponding model.

[0156] In order to keep the vent pump running efficiently, the vent pump efficiency is limited to [η min ,η max ]

[0157] η mini ≤η ij ≤η maxi ,i=1,2,…r,j=1,2…n

[0158] η ij is the operating efficiency of the vent pump j, η min is the lower limit of the vent pump operating efficiency, η maxThe upper limit of the vent pump operating efficiency

[0159] At the same time, the vent pump head H ij The maximum height L that the liquid level in the regulating tank can change H At this time, the liquid level L i and pipe head loss H s There is a numerical relationship:

[0160]

[0161] Liquid level L in the i+1th time period i+1 and the liquid level L in the i-th time period i and vent pump flow Q ij There is a numerical relationship:

[0162]

[0163] Where A is the bottom area of ​​the storage tank,

[0164] (4) Traffic Constraints:

[0165]

[0166] According to the objective function and constraint conditions, the flexible control strategy M2 for the draining pump for draining rainwater from the air conditioning storage tank at the lowest operating cost can be obtained, and M2 is started to be executed.

[0167] S33: Obtain the weather data at this time, the amount of rainwater that needs to be discharged from the storage tank, and the interval time Δt from the time when the control strategy predicts that the discharge will be completed fcst , predict the interval time Δt from now to the next rainfall when the storage tank starts to fill with water INR , if Δt INR <Δt fcst , then Δt=Δt INR Re-predict the photovoltaic output curve within Δt, and obtain the state of charge of the energy storage at this time, which is recorded as SOC 1 Go to S32; if Δt INR ≥Δt fcst Then go to S34;

[0168] S34: Determine whether the drainage of the rainwater storage tank is completed. If not, wait for Δt W After the time has passed, go to S33; upon completion, update the historical precipitation, solar radiation intensity, temperature, photovoltaic output data and historical usage data of the storage tank, and end the process of emptying the rainwater storage tank.

[0169] Δt W The minimum interval for obtaining weather data in real time is one hour, and the interval can be adjusted according to specific needs.

[0170] The above-mentioned embodiments have the ability to flexibly respond to different types of venting requirements and can formulate the best control strategy, such as optimizing control according to pipeline network dispatching instructions and real-time weather venting requirements.

[0171] Based on the same inventive concept, in other embodiments of the present invention, a low-carbon flexible control system for power distribution in a storage tank is provided. Figure 4 , including data acquisition module, optimization control module and decision execution module, specifically:

[0172] The data acquisition module obtains meteorological data of the area where the regulating reservoir is located, the use data of the regulating reservoir, historical photovoltaic output data, and the dispatching instructions of the pipe network. Based on the obtained data, the photovoltaic output curve from the end of this rainfall to the beginning of the regulating reservoir being emptied to the beginning of the next rainfall or from this time to the beginning of the next rainfall, and the remaining energy storage capacity is obtained at the same time;

[0173] The optimization control module is based on the photovoltaic output curve and the remaining power of the energy storage, with the shortest emptying time as the goal. The optimization design is limited to the use of photovoltaics and energy storage, and the emptying pump flexible control strategy M1 for emptying the air storage tank rainwater;

[0174] The decision-making execution module determines whether there is a solution to the control strategy M1. If there is a solution, the control strategy M1 is executed according to the pipeline network dispatching instructions to achieve low-carbon flexible control of power distribution in the rainwater storage tank.

[0175] The above embodiment reduces carbon emissions by comprehensively considering the energy supply of photovoltaic and energy storage to the rainwater storage tank, and introduces the mains power supply when necessary, thereby achieving the goal of low-carbon energy saving. The method and system improve energy utilization efficiency by optimizing energy configuration, thereby reducing energy consumption and carbon emissions.

[0176] The modules / units in the above examples of the present invention may specifically refer to the implementation techniques of the corresponding steps of the low-carbon flexible control method for electricity distribution in the rainwater storage tank in the above embodiments, which will not be repeated here.

[0177] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various modifications or variations within the scope of the claims, which does not affect the essence of the present invention. The above preferred features can be used in any combination without conflicting with each other.

Claims

1. A low-carbon flexible control method for electricity consumption in a rainwater storage tank, characterized in that: include: S1, obtain the meteorological data, storage pool usage data and historical photovoltaic output data of the area where the rainwater storage pool is located, and based on the obtained data, predict the photovoltaic output curve from the end of this rainfall to the beginning of the storage pool being emptied to the beginning of the next rainfall, and at the same time obtain the remaining energy storage capacity when the storage pool begins to be emptied after this rainfall; S2, based on the photovoltaic output curve and the remaining energy storage capacity, with the shortest discharge time Δt s As the goal, the optimization design is limited to the use of photovoltaic and energy storage, and the flexible control strategy M1 of the emptying pump for emptying the air storage tank rainwater; S3, determining whether there is a solution to the control strategy M1, and if there is a solution, executing the control strategy M1 according to the pipe network dispatching instruction to achieve low-carbon flexible control of power distribution in the rainwater storage tank; In S3, if the control strategy M1 has no solution or has a solution but the emptying time Δt of the pipeline dispatching instruction is o The minimum emptying time Δt required to be less than M1 s When the venting pump flexible control strategy M2 is further selected for execution, wherein the venting pump flexible control strategy M2 is based on the photovoltaic output curve and the remaining amount of energy storage, with the goal of minimizing operating costs, and optimizing the design to allow the use of photovoltaic, energy storage and city power, and determines the venting pump flexible control strategy for discharging rainwater from the air storage tank; In the process of executing the control strategies M1 and M2, according to the real-time weather conditions, it is determined whether to continue to execute the own control strategy or to re-optimize the design of the control strategy M2 and cyclically consider the real-time weather conditions to complete the execution, so as to realize the low-carbon flexible control of the power distribution of the rainwater storage tank; The S3 includes: S31, obtain the pipe network dispatching instruction for the time Δt of discharging the air storage tank o If there is no solution for the control strategy M1, take Δt=min[Δt INR ,Δt o ] Go to S32; if the control strategy M1 has a solution, take Δt=min[Δt o ,Δt s ], if Δt≠Δt s , then go to S32, if Δt=Δt s , then start executing M1 and go to S33; S32, design the objective function and its constraints with the lowest operating cost as the goal: Among them, c m For the lowest operating cost, c mi is the electricity price in the i-th time period, r is the number of time periods into which Δt is divided according to actual demand; P ej is the power that can be consumed in the i-th time period; According to the objective function and the constraint conditions, a flexible control strategy M2 for the drain pump for draining rainwater from the air storage tank at the lowest operating cost is obtained, and M2 is started to be executed; S33, obtaining the weather data at this time, the amount of rainwater Q that needs to be discharged from the storage tank, and the interval time Δt from the time when the control strategy predicts that the discharge will be completed fcst , predict the interval time Δt from now to the next rainfall when the storage tank starts to fill with water INR , if Δt INR <Δt fcst , then Δt=Δt INR Re-predict the photovoltaic output curve within Δt, obtain the state of charge of the energy storage at this time, record it as SOC1 and go to S32; if Δt INR ≥Δt fcst Then go to S34; S34, determine whether the emptying of the storage tank is completed. If not, wait for Δt W After the time has passed, the process goes to S33; when completed, the historical precipitation, solar radiation intensity, temperature, photovoltaic output data and historical usage data of the storage tank are updated, and the emptying process of the rainwater storage tank is ended; The constraints include energy constraints, energy storage constraints, venting pump efficiency constraints and flow constraints; Wherein, the energy constraint is: The total energy consumed by the emptying pump of the storage tank in the i-th time period is less than or equal to the consumable energy in the time period: W ei is the energy that can be consumed in the i-th time period, W i is the total energy consumed by the venting pump in the i-th time period, P ij is the power of the jth vent pump in the i-th time period, and n is the number of vent pumps; The consumable energy in the i-th time period is the sum of the dischargeable energy of photovoltaic and energy storage in this time period: W ei =Δt f ×(P PVi +P ESSi ),i=1,2,…r Where P PVi is the average value of the predicted photovoltaic output curve in the i-th time period, P ESSi is the average discharge power of the energy storage in the i-th time period; Wherein, the energy storage constraint is: Among them, SOC i+1 =g1(SOC i ,P ESSi ), SOC i is the energy storage charge state in the i-th time period, and g1 represents the SOC in the i+1-th time period. i+1 and SOC in the i-th time period i and discharge power P ESSi About P ESS_max is the maximum discharge power of the energy storage battery, SOC min is the minimum value of the energy storage state of charge, SOC max is the maximum value of the energy storage charge state; Wherein, the vent pump efficiency constraint is: Adjust frequency f ij To achieve the venting pump power P ij Flexible adjustment, where f ij is the frequency of the jth venting pump in the i-th time period, Q ij is the discharge flow rate of the jth discharge pump in the i-th time period, H ij is the j-th vent pump head in the i-th time period, η ij is the operating efficiency of the jth venting pump in the i-th time period, L i The liquid level of the storage tank in the i-th time period, η min is the lower limit of the vent pump operating efficiency, η max It is the upper limit of the operating efficiency of the vent pump; g2 represents the venting pump power P ij With its f ij , Q ij , H ij , η ij There is a functional relationship; g3 represents the head of the venting pump H ij With L i , Q ij There is a functional relationship; g4 represents the i+1th time period L i+1 and the i-th time period L i And the venting flow rate Q of the venting pump ij related; The flow constraint is:

2. The low-carbon flexible control method for electricity consumption in rainwater storage tanks according to claim 1 is characterized in that: Said S1 comprises: Obtain meteorological data, historical usage data of the rainwater storage pool, and historical photovoltaic output data. The meteorological data include: historical precipitation, solar radiation intensity, and temperature data of the area where the rainwater storage pool is located; current precipitation, solar radiation intensity, and temperature data; and future precipitation, solar radiation intensity, and temperature forecast data obtained from the local meteorological station; According to the meteorological data and historical usage data of the regulating reservoir, it is predicted that the interval time Δt between the end of this rainfall and the beginning of the emptying of the regulating reservoir and the beginning of the filling of the regulating reservoir at the next rainfall is INR ; According to the meteorological data and historical photovoltaic output data, it is predicted that the interval time Δt from the end of this rainfall to the beginning of the reservoir being emptied to the beginning of the next rainfall is INR The internal photovoltaic output curve; at the same time, the charge state SOC1 when the energy storage reservoir starts to be emptied after the rainfall ends is obtained.

3. The low-carbon flexible control method for electricity consumption in rainwater storage tanks according to claim 2 is characterized in that: The S2 comprises: Get the amount of rainwater Q that needs to be discharged from the rainwater storage tank at this time; Design an objective function with the shortest emptying time as the goal, specifically: Δt s =min(s×Δt f ) Among them, 0≤s≤k, k is the value of Δt INR The number of time periods divided according to actual demand, s is the number of empty time periods, Δt s is the shortest emptying time, Δt f Δt INR The length of the time period divided by actual demand, assuming that each variable is in Δt f The inside remains unchanged; Designing constraints of the objective function; The flexible control strategy M1 of the draining pump for draining rainwater from the air-conditioning storage tank within the shortest draining time is calculated according to the objective function and the constraint conditions.

4. The low-carbon flexible control method for electricity consumption in rainwater storage tanks according to claim 3 is characterized in that: If there is any consumable energy left in any time period, it will be fed to the mains; Among them, the consumable energy in the i-th time period is: W ei =Δt f ×(P PVi +P ESSi ),i=1,2,…k The remaining consumable energy in the i-th time period is: When W s >0, then W s Feed to mains electricity.

5. The low-carbon flexible control method for electricity consumption in rainwater storage tanks according to claim 1 is characterized in that: The S3 includes: S301, obtaining the pipe network dispatching instruction for discharging the air storage tank for a time Δt o , when the control strategy M1 has a solution, let Δt=min[Δt o ,Δt s ] and when Δt=Δt s When , M1 starts to execute; S302, obtaining the weather data at this time, the amount of rainwater Q that needs to be discharged from the storage tank, and the interval time Δt from the time when the control strategy predicts that the discharge will be completed fcst , predict the interval time Δt from now to the next rainfall when the storage tank starts to fill with water INR , if Δt INR ≥Δt fcst Then go to S303; S303, determine whether the emptying of the storage tank is completed. If not, wait for Δt W After the time has passed, go to S302; upon completion, update the historical precipitation, solar radiation intensity, temperature, photovoltaic output data and historical usage data of the regulating reservoir, and end the current regulating reservoir emptying process.

6. A low-carbon flexible control system for power distribution in a rainwater storage tank, using the method according to any one of claims 1 to 5, characterized in that: include: Data acquisition module, which obtains meteorological data of the area where the regulating reservoir is located, the use data of the regulating reservoir, historical photovoltaic output data, and the dispatching instructions of the pipe network. Based on the acquired data, it predicts the photovoltaic output curve from the time when the regulating reservoir starts to be emptied after the end of this rainfall to the time when the regulating reservoir starts to be filled with water after the next rainfall, or from this time to the time when the regulating reservoir starts to be filled with water after the next rainfall, and obtains the remaining energy storage capacity at the same time; An optimization control module, based on the photovoltaic output curve and the remaining energy storage capacity, with the shortest emptying time as the goal, optimizes the design of a flexible control strategy M1 for the emptying pump for emptying the rainwater in the air storage tank when photovoltaic and energy storage are used only; A decision-making execution module determines whether there is a solution to the control strategy M1. When a solution exists, the control strategy M1 is executed according to the pipeline network dispatching instruction to achieve low-carbon flexible control of the power distribution of the rainwater storage tank.

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