Plant-station joint control optimization dispatching method for large-scale reconstruction and expansion of water supply network

Abstract

The present invention discloses a "plant-station" joint control optimization scheduling method for serving large-scale reconstruction and expansion of water supply pipelines, comprising the following steps: (1) determining the time range for optimization scheduling, which is usually 24 hours a day; (2) obtaining the parameters of the water pump units of the water plant and the regional booster pump station, and calculating the water pump characteristic curve; (3) determining the constraints of the "plant-station" joint control optimization scheduling model; (4) establishing a "plant-station" joint control optimization scheduling model for the water supply pipeline network, and using an artificial bee colony algorithm to solve the optimal operation plan; (5) comparing multiple groups of operation plans to obtain the optimal operation plan for the current pipeline network.

Description

Technical Field

[0001] The present invention belongs to the field of urban water supply network optimization and dispatching, and in particular to a "plant-station" joint control optimization and dispatching method serving large-scale reconstruction and expansion of water supply network. Background Art

[0002] With the development of urbanization, the reform of urban-rural integrated water supply is constantly advancing. Urban-rural integrated water supply means that urban water supply pipelines are constantly extended and the scope of water supply is constantly expanding. How to reduce the operating energy consumption of the water supply network under the conditions of expanding the pipeline network and centralized water supply has become a major problem in the construction of urban-rural integrated water supply. In the past, researchers have conducted a lot of research on the optimal combination of the operating status of water plant pump units, and set the operating status of different pumps under different working conditions to avoid energy waste. In recent years, some researchers have been committed to improving the calculation speed of the optimization scheduling model for real-time scheduling applications, but most of these studies are aimed at water plant pump room pump units alone. In the urban-rural integrated water supply system, the distance from the water plant to the end of the pipeline network is long, and it is usually necessary to set up a regional booster pump station in the middle. If the operating mechanism of the booster pump station is not scientific enough, energy waste will occur. Therefore, the optimization scheduling of water plant pump units alone can no longer meet the energy saving needs of the urban-rural integrated water supply system. The regional booster pump station is connected between the water plant and the users, which improves the insufficient water pressure in some local areas. It is an important link in the water supply system. If the linkage relationship between the water plant and the regional booster pump station can be utilized and the water plant and the regional booster pump station can be jointly controlled and dispatched, it will be of great significance to the energy saving of the water pump units in the urban and rural integrated water supply system. Summary of the invention

[0003] The present invention provides a "plant-station" joint control optimization scheduling method serving the large-scale reconstruction and expansion of water supply pipelines. An artificial bee colony algorithm is used to search for the optimal operation plan of water plants and regional pumping stations, thereby achieving lower pipeline operation energy consumption costs and more uniform pressure distribution.

[0004] The "plant-station" joint control optimization dispatching method serving the large-scale reconstruction and expansion of the water supply network includes the following steps:

[0005] (1) Select the optimized scheduling time range: Determine the time range for optimized scheduling, usually 24 hours a day.

[0006] (2) Calculate the pump characteristic curve: Obtain the pump unit parameters of the water plant and regional booster station. The operating conditions of the pump are based on the pump head-flow and efficiency-flow characteristic curves, which can be expressed by the following quadratic polynomial:

[0007] h=a0-a1Q 2

[0008] η=b0+b1Q+b2Q 2

[0009] In the formula, h, Q, η——water pump head, flow rate, efficiency;

[0010] a0, a1, b0, b1, b2——constant coefficients.

[0011] The variable speed pump can respond to changes in working conditions by adjusting the speed, and maintain operation in the high-efficiency zone under different water supply flow rates. It is more energy-efficient than the fixed-speed pump when the water supply is small. Assuming that the rated speed of the variable speed pump is set to n0 and the current speed is n1, the flow rate and head before and after speed regulation meet the following requirements:

[0012] S1=n1 / n0

[0013] Q1 / Q0=S1

[0014] h1 / h0=(S1) 2

[0015] When the speed of the variable frequency pump is n1, the head-flow and efficiency-flow characteristic curves are:

[0016]

[0017] η1=b0+b1Q1 / S1+b2(Q1 / S1) 2

[0018] Where, Q1, h1, η1 – flow rate, head, efficiency corresponding to the current speed;

[0019] Q0, h0, η0 - flow rate, head and efficiency under rated conditions.

[0020] (3) Determine the constraints of the “plant-station” joint control optimization scheduling model:

[0021] Constraints of the hydraulic balance equation of the pipe network:

[0022] G(H,Q)=0

[0023] Constraints on water plant’s water supply capacity:

[0024] k min Q ni ≤Q ni ≤k max Q ni

[0025] In the formula, Q′ ni ——Original water supply of water plant n at time i;

[0026] Q ni ——The output water supply of the water plant model at time i;

[0027] k min , kmax ——The upper and lower limit coefficients of water supply are 0.7 and 1.3.

[0028] Nodal pressure constraints:

[0029] The node pressure constraint includes the minimum service head constraint of each user node and the minimum water pressure constraint of the upstream node of the pump station site selection (to avoid the impact of regional pump station operation on upstream pressure):

[0030] H j >H j，min

[0031] H k >H k，min

[0032] In the formula, H j ——pressure at node j;

[0033] H j，min ——the minimum service head of node j;

[0034] H k ——pressure at node k upstream of the booster station;

[0035] H k，min ——Minimum water inlet pressure at node k upstream of the booster pump station;

[0036] (4) Application of optimization scheduling model: Establish a water supply network "plant-station" joint control optimization scheduling model, and use the artificial bee colony algorithm to solve the optimal operation plan of the water plant and regional booster pump station. The objective function of the water supply network "plant-station" joint control optimization scheduling model is as follows:

[0037] The goal is to minimize the annual conversion cost of water plant and regional booster station operating energy consumption, as shown in the following formula:

[0038]

[0039] In the formula, E is the electricity cost, RMB / kWh; ρ is the density of water; g is the acceleration due to gravity;

[0040] t——the tth time period, t=1,...T, T=24;

[0041] n——the nth water plant, n=1, 2, ...N;

[0042] np——the pth water pump of the nth water plant, np=1,...NP;

[0043] Q npt ——The water supply of the pth pump in the nth water plant in the tth period;

[0044] H npt——The discharge head of the pth water pump in the nth water plant in the tth period;

[0045] η npt ——The efficiency of the pth pump in the nth water plant in the tth period;

[0046] Q mt ——The amount of water lifted by the mth booster pump station in time period t;

[0047] H mt ——The lifting head of the m-th booster pump station in time period t;

[0048] η mt ——The operating efficiency of the mth booster pump station in period t.

[0049] (5) Compare multiple groups of operation plans to obtain the optimal operation plan for the current pipeline network.

[0050] Beneficial effects of the present invention:

[0051] The "plant-station" joint control optimization scheduling method of the present invention, which serves the large-scale reconstruction and expansion of water supply pipelines, constructs an objective function that takes into account the operating energy consumption costs of water pump units in water plants and regional booster pump stations. Through a series of processes such as time range selection, water pump characteristic curve calculation, and model establishment, an artificial bee colony algorithm is used to solve the optimization model. The final generated water plant and regional pump station operation plan effectively reduces the total energy consumption costs of pipeline network operation and reduces the average pressure of the pipeline network. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a wireframe flow chart of the "plant-station" joint control optimization scheduling method for serving the large-scale reconstruction and expansion of the water supply network according to this embodiment.

[0053] Figure 2 This is the H city water supply network diagram in the "plant-station" joint control optimization scheduling method for serving the large-scale reconstruction and expansion of the water supply network in this embodiment.

[0054] Figure 3 Schematic diagram of the decision variable encoding form.

[0055] Figure 4 This is a comparison chart of scheduling results.

[0056] Figure 5 The following is a comparison chart of the actual plan and dispatch plan of TH Water Plant at each moment.

[0057] Figure 6 This is a comparison chart between the actual plan and the scheduling plan of the booster pump station at each moment.

[0058] Figure 7 Pressure distribution diagram before scheduling at a certain moment.

[0059] Figure 8 Pressure distribution diagram after scheduling at a certain moment. DETAILED DESCRIPTION

[0060] The implementation of the present invention is further described in detail below with reference to the accompanying drawings and examples.

[0061] like Figure 1 As shown, the specific steps of the "plant-station" joint control optimization scheduling method for serving large-scale reconstruction and expansion of water supply pipe networks in this embodiment are as follows:

[0062] Step 1. Select the optimized scheduling time range: Take February 2, 2020, 24 hours a day as an example for optimized scheduling.

[0063] Step 2: Calculate the pump characteristic curve.

[0064] The water supply network of H City is supplied by CB Water Plant, CX Water Plant and TH Water Plant. The three water plant pump houses have a total of 16 water pumps, including 12 fixed-speed pumps and 4 variable-frequency pumps. The regional booster pump station contains 3 variable-frequency pumps.

[0065] CB Water Plant: 1#, 4#, 5# are fixed speed pumps, 2#, 3# are variable frequency pumps, and the specific rated information is shown in Table 1:

[0066] Table 1 CB water plant pump room pump information

[0067] serial number Rated flow rate (L / s) Rated head (m) Rated electromechanical power (kW) 1# 1111 38 500 2#(Frequency conversion) 1111 38 500 3#(Frequency conversion) 2064 38 900 4# 2064 38 900 5# 495 38 240

[0068] According to the rated flow and head of the water pump, we know that the two specific points on the (head-flow) characteristic curve of the 1# water pump are (1111, 38) and (2222, 0). Substituting into the characteristic curve function, we can get the (head-flow) characteristic curve of the 1# water pump:

[0069] h=50.67-1.026×10 -5 Q 2

[0070] According to the pump efficiency formula: η=ρgQH / P, P is shaft power=electromechanical power / safety margin, and the safety margin is randomly selected from 1.05-1.2. g = 9.8m / s. Substituting the rated flow and head into the above formula, we can get the efficiency η0 under the rated state. It can be seen that the two specific points on the 1# water pump (efficiency-flow) characteristic curve are (1111, η0) and (2222, 0). Substituting into the characteristic curve function, we can get the 1# water pump (efficiency-flow) characteristic curve:

[0071] η=-7.372×10 -5 Q 2 +0.164Q

[0072] Similarly, the head-flow and efficiency-flow characteristic curves of the 4# water pump can be obtained:

[0073] h=50.67-2.974×10 -6 Q 2

[0074] η=-2.136×10 -5 Q 2 +0.088Q

[0075] The head-flow and efficiency-flow characteristic curves of the 5# water pump:

[0076] h=50.67-5.17×10 -5 Q 2

[0077] η=-3.55×10 -4 Q 2 +0.351Q

[0078] The characteristic curves of variable frequency pumps 2# and 3# are not fixed. The characteristic curves under rated working conditions are the same as those of 1# and 4#, respectively. The characteristic curves under other working conditions change according to the change of speed. The details are as follows, which can be calculated by calling the EPAnet toolbox:

[0079] By obtaining the pump head, flow rate, and power, the pump head-flow characteristic curve can be calculated and expressed by the following quadratic polynomial:

[0080] Assume that the rated speed of the variable frequency pump is set to n0, and the current speed is n1. The flow rate and head before and after speed regulation meet the following conditions:

[0081] S1=n1 / n0

[0082] Q1 / Q0=S1

[0083] h1 / h0=(S1) 2

[0084] When the speed of the variable frequency pump is n1, the head-flow and efficiency-flow characteristic curves are:

[0085]

[0086] η1=b0+b1Q1 / S1+b2(Q1 / S1) 2

[0087] Where, Q1, h1, η1 – flow rate, head, efficiency corresponding to the current speed;

[0088] Q0, h0, η0 - flow rate, head and efficiency under rated conditions.

[0089] CX Water Plant: All 1# to 5# water pumps are fixed speed pumps, and their specific rated information is shown in Table 2:

[0090] Table 2 CX water plant pump room pump information

[0091] serial number Rated flow rate (L / s) Rated head (m) Rated electromechanical power (kW) 1#、2#、3# 361 37 180 4#、5# 561 35 250

[0092] According to the rated flow, head and power of the water pump, the head-flow and efficiency-flow characteristic curves of 1#, 2# and 3# water pumps are obtained:

[0093] h=49.33-9.465×10 -5 Q 2

[0094] η=-6.6×10 -4 Q 2 +0.476Q

[0095] Head-flow and efficiency-flow characteristic curves of 4# and 5# water pumps:

[0096] h=46.67-3.708×10 -5 Q 2

[0097] η=-2.796×10 -4 Q 2 +0.314Q

[0098] TH Water Plant: 1#, 2#, 3#, 4# are fixed speed pumps, 5#, 6# are variable frequency pumps. For specific rated information, see Table 3:

[0099] Table 3 TH Water Plant Pump Room Pump Information

[0100] serial number Rated flow rate (L / s) Rated head (m) Rated electromechanical power (kW) 1#、2#、3#、4# 1670 39 800 5#, 6# (frequency conversion) 1000 41 500

[0101] According to the rated flow, head and power of the water pump, the head-flow and efficiency-flow characteristic curves of 1#, 2#, 3# and 4# water pumps are obtained:

[0102] h=52.00-4.662×10 -6 Q 2

[0103] η=-3.0478×10 -5 Q 2 +0.102Q

[0104] Head-flow and efficiency-flow characteristic curves of 5# and 6# at rated working conditions:

[0105] h=54.67-1.367×10 -5 Q 2

[0106] η=-8.5×10 -5 Q 2 +0.17Q

[0107] Booster pump station: The three booster pump station water pumps 1#~3# are all variable frequency pumps. The specific rated information is shown in Table 4:

[0108] Table 4 Booster station water pump information

[0109]

[0110] According to the rated flow, head and power of the water pump, the characteristic curve of the 1# water pump under rated working conditions is obtained:

[0111] h=40-1.563×10 -5 Q 2

[0112] η=-1.347×10 -4 Q 2 +0.216Q

[0113] The head-flow and efficiency-flow characteristic curves of the 2# water pump at rated working conditions are:

[0114] h=40-2.5×10 -4 Q 2

[0115] η=-2.144×10 -3 Q 2 +0.858Q

[0116] The head-flow and efficiency-flow characteristic curves of the 3# water pump at rated working conditions:

[0117] h=40-1.0×10 -3 Q 2

[0118] η=-8.823×10 -3 Q 2 +1.765Q

[0119] Step 3: Determine the constraints of the “plant-station” joint control optimization scheduling model:

[0120] Constraints of the hydraulic balance equation of the pipe network:

[0121] G(H,Q)=0

[0122] Constraints on water plant’s water supply capacity:

[0123] k min Q ni ≤Q ni≤k max Q ni

[0124] In the formula, Q′ ni ——Original water supply of water plant n at time i;

[0125] Q ni ——The output water supply of the water plant model at time i;

[0126] k min , k max ——The upper and lower limit coefficients of water supply are 0.7 and 1.3.

[0127] Nodal pressure constraints:

[0128] The node pressure constraint includes the minimum service head constraint of each user node and the minimum water pressure constraint of the upstream node of the pump station site selection (to avoid the impact of regional pump station operation on upstream pressure):

[0129] H j >H j，min

[0130] H k >H k，min

[0131] In the formula, H j ——pressure at node j;

[0132] H j，min ——the minimum service head of node j;

[0133] H k ——The pressure of node k upstream of the booster station is 0.18Mpa based on the pipe network survey of City H;

[0134] H k，min ——The minimum water pressure at the upstream node k of the booster pump station is 0.1Mpa after investigation;

[0135] Step 4: Application of regional pump station optimization site selection model.

[0136] The speed of the water pump station pump and the regional booster station pump are used as decision variables. The fixed speed pump contains two variable values ​​0 and 1, 0 represents off, 1 represents on. Considering that the variable frequency pump should be operated in the high efficiency area as much as possible, the speed range of the variable frequency pump is [0, 0.75, 0.76, ... 0.98, 0.99, 1], with a total of 27 variable values. All variables are discrete variables, and the variable expression form is as follows Figure 3, establish a "plant-station" optimization scheduling model for the water supply network, use the artificial bee colony algorithm to solve the optimal operation plan of the water plant and regional booster pump station, and use the EPAnet tool to complete the hydraulic leveling during the calculation of the water supply network plant-station joint control optimization scheduling model. The objective function of the water supply network plant-station joint control optimization scheduling model is as follows:

[0137] The goal is to minimize the annual conversion cost of water plant and regional booster station operating energy consumption, as shown in the following formula:

[0138]

[0139] In the formula, E is the electricity cost, RMB / kWh; ρ is the density of water; g is the acceleration due to gravity;

[0140] t——the tth time period, t=1,...T, T=24;

[0141] n——the nth water plant, n=1, 2, ...N;

[0142] np——the pth water pump of the nth water plant, np=1,...NP;

[0143] Q npt ——The water supply of the pth pump in the nth water plant in the tth period;

[0144] H npt ——The discharge head of the pth water pump in the nth water plant in the tth period;

[0145] η npt ——The efficiency of the pth pump in the nth water plant in the tth period;

[0146] Q mt ——The amount of water lifted by the mth booster pump station in time period t;

[0147] H mt ——The lifting head of the m-th booster pump station in time period t;

[0148] η mt ——The operating efficiency of the mth booster pump station in period t.

[0149] Step 5: Compare multiple groups of operation plans to obtain the optimal operation plan for the current pipe network. Figure 4 The following is a comparison chart of the annual energy consumption cost of the pipeline network before and after the optimal solution is dispatched at different times of the day. Figure 4 It can be seen that the economic indicator values ​​of the optimal solution obtained in each period are significantly lower than those of the original pipeline network.

[0150] Table 5 is a comparison of the specific conversion values ​​of the annual conversion operation energy consumption costs of the pipeline network at various times before and after the dispatch (T is the total energy consumption conversion economic index, and DRT is the reduction rate of the total conversion economic index):

[0151] Table 5 Comparison of optimization results at different times

[0152]

[0153]

[0154] It can be seen from Table 5 that the T value at each moment is reduced after optimization. Comprehensively considering all moments, the total T value reduction rate is 10.13%, that is, the energy consumption cost reduction rate for the whole day. The total annual energy consumption reduction cost of the optimal solution is 2.76327 million.

[0155] Compare the scheduling plan with the actual plan. For the comparison, see Figure 5-Figure 8 .from Figure 5 It can be seen that the water supply pressure of TH Water Plant in each period of the scheduling plan is significantly reduced, while the water supply pressure of TH Water Plant in the actual plan remains unchanged throughout the day. TH Water Plant in H City is a newly built water plant in recent years. In order to maintain the absolute safety of water supply in its water supply area, TH Water Plant has always maintained high-pressure water discharge. In order to avoid the occurrence of pipe bursts in high-pressure areas, a pressure reducing valve is set in front of the area near TH Water Plant. In this process, the water pressure is immediately released after it is increased, resulting in energy waste. The scheduling plan makes full use of the two variable frequency pumps in the pump room of TH Water Plant, so that the water supply pressure of TH Water Plant changes throughout the day with the changes in the water demand of the pipeline network, which directly reduces the water supply energy consumption of TH Water Plant.

[0156] Figure 6 The following is a comparison chart of the actual scheme and the dispatching scheme of the booster pump station. The water supply pressure here is the average outlet pressure of all booster pump stations, and the water supply volume is the total water lifting volume of all booster pump stations. Figure 6 It can be seen that the average outlet pressure of the booster pump station in each period of the scheduling scheme has dropped significantly. The total lifting water volume of the booster pump station in each period has also dropped significantly. The reduction in the operating cost of the booster pump station in the scheduling scheme has made a huge contribution to the reduction of the total cost.

[0157] pass Figure 7 and Figure 8 By comparison, we can see that after the dispatch, the average pressure of the pipeline network nodes decreased, the area of ​​the high-pressure block decreased, and the low-pressure area of ​​the pipeline network was also filled. After the dispatch, the node pressure of the pipeline network was basically concentrated between 0.2Mpa and 0.3Mpa. It can be seen that the "plant-station" joint control optimization dispatch model has contributed to the pressure regulation of the pipeline network.

[0158] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A plant-station joint control optimization dispatching method serving large-scale reconstruction and expansion of water supply pipe networks, characterized in that: The following steps are involved: (1) Determine the time range for which optimized scheduling is required, where the time range is 24 hours a day; (2) Obtain the parameters of the water pump units in the water plant and regional booster pump station, and calculate the pump characteristic curve; If the water pumps in the water plant and regional booster station water pump units are fixed-speed pumps, the head-flow and efficiency-flow characteristic curves of the water pumps can be calculated by obtaining the rated head, flow, and power of the water pumps, which can be expressed by the following quadratic polynomial: In the formula, ——Water pump head, flow rate and efficiency; ——constant coefficient; (3) Determine the constraints of the plant-station joint control optimization scheduling model; The constraints of the water supply network plant-station joint control optimization scheduling model are as follows: Constraints of the hydraulic balance equation of the pipe network: Constraints on water plant’s water supply capacity: In the formula, —— time The original water supply of the water plant; —— time The water plant model outputs water supply; ——The upper and lower limit coefficients of water supply are 0.7 and 1.3; Nodal pressure constraints: The node pressure constraint includes the minimum service head constraint of each user node and the minimum water pressure constraint of the upstream node of the pump station site: In the formula, --node pressure; --node Minimum service head; ——Upstream node of booster station pressure; ——Upstream node of booster station Minimum water pressure; (4) Establish a water supply network plant-station joint control optimization scheduling model and use the artificial bee colony algorithm to solve the optimal operation plan of the water plant and regional booster pump station; Taking the speed of the water pump station pump of the water plant and the water pump station pump of the regional booster pump station as the decision variable, the "plant-station" optimization scheduling model of the water supply network is established, and the artificial bee colony algorithm is used to solve the optimal operation plan of the water plant and the regional booster pump station. The EPAnet tool is used to complete the hydraulic leveling during the calculation process of the plant-station joint control optimization scheduling model of the water supply network; the objective function of the plant-station joint control optimization scheduling model of the water supply network is as follows: The goal is to minimize the annual conversion cost of operating energy consumption of water plants and regional booster pump stations, as shown in the following formula: In the formula, ——Electricity fee, RMB / kWh; - water density; - acceleration due to gravity; ——No. time period, ; ——No. A water plant, ; ——No. The first water plant A water pump, ; ——No. The first water plant The water pump Water supply during the period; ——No. The first water plant The water pump The water head during the period; ——No. The first water plant The water pump Efficiency of time slots; ——No. Booster pump station The amount of water raised during each period; ——No. Booster pump station Lifting head during the period; ——No. Booster pump station Operational efficiency of the time period; (5) Compare multiple groups of operation plans to obtain the optimal operation plan for the current pipeline network.

2. The plant-station joint control optimization scheduling method for serving large-scale reconstruction and expansion of water supply pipe network as claimed in claim 1 is characterized in that: In step (2), if the water pumps in the water plant and regional booster station water pump units are variable frequency pumps, the head-flow and efficiency-flow characteristic curves of the water pumps are calculated by obtaining the rated head, flow, and power of the water pumps, which can be expressed by the following quadratic polynomial: Assume that the rated speed of the variable frequency pump is set to , the current speed is , the flow rate and head before and after speed regulation meet the following requirements: The variable frequency pump is at a speed of When the head-flow and efficiency-flow characteristic curves are: In the formula, ——Flow rate, head and efficiency corresponding to the current speed; ——Flow rate, head and efficiency under rated conditions.

3. The plant-station joint control optimization scheduling method for serving large-scale reconstruction and expansion of water supply pipe network as claimed in claim 1 is characterized by: The decision variables in step (4): The fixed speed pump has two variable values ​​0 and 1, 0 represents off and 1 represents on; considering that the variable frequency pump should be operated in the high efficiency zone as much as possible, the range of the variable frequency pump speed is , a total of 27 variables, all of which are discrete variables.

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