Optimized scheduling method, system, storage medium and equipment for energy consumption digital twinborn model of sewage treatment plant

Abstract

The invention belongs to the technical field of electric energy utilization, and provides an optimal scheduling method, system, storage medium and equipment for an energy consumption digital twinborn model of a sewage treatment plant, and the method comprises the steps: carrying out the pretreatment of a sewage treatment system, and constructing a technological process architecture of the sewage treatment plant; according to the process flow architecture of the sewage treatment plant, constructing an energy consumption digital twinborn model of each sewage treatment link; a sewage treatment plant day-ahead optimization scheduling model under the power market background is constructed by considering the condition of the power market background and combining with the power demand response market. According to the method, the problem of research on an optimal scheduling method under a power market environment under a specific industrial load is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric energy utilization and relates to an optimization scheduling method, system, storage medium and equipment for a digital twin model of energy consumption in a sewage treatment plant. Background Art

[0003] Industrial and commercial users are facing great pressure to save energy and reduce costs in the context of green and low-carbon transformation. They need to take a series of measures to reduce energy consumption and carbon emissions to meet global climate change goals and regulatory requirements, which is crucial for the sustainable development and competitiveness of industrial and commercial users. In addition to measures such as equipment energy-saving transformation and renewable energy utilization, industrial and commercial users can participate in the electricity market by utilizing their own flexibility resources, thereby better managing electricity procurement costs.

[0004] However, at present, industrial and commercial users participating in the power market face difficulties such as further clarifying the adjustable capacity of resources, deepening the understanding of policies and rules, increasing technology and cost investment, and improving the level of refined management and automatic control. At the same time, most of the relevant data at home and abroad are aimed at conventional demand-side distributed resource research, but there are few related research and application cases for flexible resources and demand response for industrial loads. Therefore, it is of great value and significance to carry out research on optimal dispatching methods in the power market environment for specific industrial loads. Summary of the invention

[0005] In order to solve the above problems, a method, system, storage medium and device for optimizing the scheduling of a digital twin model of energy consumption in a sewage treatment plant are provided.

[0006] In the first aspect, the present invention provides an optimization scheduling method for a digital twin model of energy consumption in a sewage treatment plant, which adopts the following technical solutions:

[0007] Pre-treat the sewage treatment system and build the process flow structure of the sewage treatment plant;

[0008] According to the process architecture of the sewage treatment plant, a digital twin model of energy consumption in each sewage treatment link is constructed;

[0009] Considering the electricity market background and combining it with the electricity demand response market, a day-ahead optimal scheduling model for sewage treatment plants is constructed under the electricity market background.

[0010] Preferably, the process flow architecture of the sewage treatment plant is constructed, comprising the following steps:

[0011] Analyze the electrical equipment required to build the process architecture;

[0012] According to the selected candidate modeling equipment, analyzing the adjustable capacity of the power consumption of these candidate modeling equipment;

[0013] Analyze energy storage devices in sewage treatment systems;

[0014] Construct the architecture of the digital twin model of energy consumption of the sewage treatment plant.

[0015] Preferably, the analysis and construction of electrical equipment required for the process flow architecture specifically includes:

[0016] Obtain the historical electricity consumption data of the sewage treatment system and calculate the electricity consumption proportion EUP of each electrical equipment in the sewage treatment system v ;

[0017] Set the conditions for the electrical equipment to build the process flow architecture to meet EUP v ≥θ, then the electrical equipment is used as an alternative modeling equipment;

[0018] Among them, θ is the minimum electricity consumption ratio of the electrical equipment required to build the process flow architecture.

[0019] Preferably, the process flow architecture of the sewage treatment plant includes: a pretreatment lift pump, a hydrolysis acidification tank, a hydrolysis acidification equipment, a biochemical treatment tank, a biochemical treatment equipment, an aeration fan, a filter tank, a filter disinfection equipment, a tailwater tank, a tailwater lift pump, and an inlet tank.

[0020] Preferably, the pretreatment boost pump is a variable frequency speed regulation device, and the power consumption of the pretreatment boost pump and its own pumping flow rate satisfy the following formula:

[0021]

[0022] in, is the power consumption of all pretreatment boost pumps during period t; is the rated pumping flow of the i-th pretreatment lift pump; is the rated power consumption of the i-th pretreatment boost pump; represents the power consumption of the i-th pretreatment boost pump; Represents the water flow rate pumped out by the i-th pretreatment lift pump.

[0023] Preferably, the aeration fan is a variable frequency speed regulating device, and the power consumption of the aeration fan and its air supply volume satisfy the following formula:

[0024]

[0025] in, is the power consumption of all aeration fans during period t; is the rated air delivery volume of the jth aeration fan in period t; is the rated power consumption of the jth aeration fan in period t; Represents the air supply of the i-th aeration fan.

[0026] Preferably, the construction obtains a day-ahead optimal dispatch model for a sewage treatment plant under the background of the power market, and the objective function of the optimal dispatch method is cost minimization, which satisfies the following formula:

[0027]

[0028] Where C is the operating cost; R is the income from participating in the electricity demand response market; p t To predict the time-of-use electricity price in the electricity market; represents the forecasted subsidy price for the electricity demand response market; It represents the total electricity consumption of the adjustable part of the sewage treatment plant;

[0029] P base,t It represents the operation baseline of the sewage treatment plant; Δt is the time period length. If one time period is 1 hour, the whole day can be divided into 24 time periods. max =24.

[0030] In the second aspect, the present invention provides an optimization scheduling system for a digital twin model of energy consumption in a sewage treatment plant, which adopts the following technical solutions:

[0031] An optimization scheduling system for a digital twin model of energy consumption of a sewage treatment plant, the system comprising a construction module of a process flow architecture of a sewage treatment plant, a construction module of a digital twin model of energy consumption of a sewage treatment plant, and a construction module of a day-ahead optimization scheduling method of a sewage treatment plant;

[0032] The construction module of the process flow architecture of the sewage treatment plant is used to pre-treat the sewage treatment system and construct the process flow architecture of the sewage treatment plant;

[0033] The construction module of the digital twin model of energy consumption of sewage treatment plants is used to construct the digital twin model of energy consumption of each sewage treatment link according to the process flow architecture of the sewage treatment plant;

[0034] The construction module of the sewage treatment plant day-ahead optimal scheduling method is used to consider the power market background and combine it with the power demand response market to construct a day-ahead optimal scheduling model for sewage treatment plants under the power market background.

[0035] In a third aspect, the present invention provides a computer storage medium, which adopts the following technical solution:

[0036] A computer storage medium stores one or more programs. When the one or more programs are executed, the above-mentioned optimization scheduling method of the digital twin model of energy consumption of a sewage treatment plant can be implemented.

[0037] In a fourth aspect, the present invention provides a device, which adopts the following technical solution:

[0038] A device includes a processor, a communication interface, a memory and a communication bus; the processor, the communication interface and the memory communicate with each other via the communication bus; the memory stores at least one program in the computer storage medium that can be loaded and executed by the processor.

[0039] In summary, the present invention includes the following beneficial technical effects:

[0040] 1. The present invention combines the analysis results of the process flow architecture, equipment adjustable capacity, energy storage equipment, etc. of the sewage treatment system, and constructs the energy consumption digital twin model architecture of the sewage treatment plant through pretreatment, which helps to better grasp the effective resources in the sewage treatment plant and provide space for subsequent optimization and scheduling;

[0041] 2. The present invention constructs the energy consumption digital twin model architecture of the sewage treatment plant. Based on the energy consumption digital twin model, the energy consumption characteristics of the main adjustable equipment in each link of the sewage treatment plant are fully reflected, and it has broad application prospects. For example, it can be used to carry out a series of studies on sewage treatment plant optimization scheduling, comprehensive energy management, green and low-carbon development, etc.

[0042] 3. The optimization scheduling method of the present invention aims at minimizing costs, comprehensively considers the market time-of-use electricity prices and electricity demand response subsidies, and formulates a day-ahead optimization scheduling plan for the sewage treatment plant. This optimization scheduling method fully considers the characteristics of the electricity market, helps to reduce the energy costs of sewage treatment plants, and enhances the competitiveness of enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A flow chart of an optimization scheduling method for a digital twin model of energy consumption in a sewage treatment plant is disclosed.

[0044] Figure 2 A flow chart of the main process of sewage treatment is disclosed.

[0045] Figure 3 A flow chart for constructing a digital twin model of energy consumption in a sewage treatment plant is disclosed.

[0046] Figure 4 A schematic diagram of the relationship between the inflow and outflow flow rates of a water inlet pool, the water storage status and the price is disclosed.

[0047] Figure 5 A schematic diagram showing the relationship between the inflow and outflow flow rates of the hydrolysis acidification tank, biochemical treatment tank, filtration tank and tailwater tank, as well as the water storage status and price is disclosed.

[0048] Figure 6 A schematic diagram of electrical power consumption of equipment in various links is disclosed.

[0049] Figure 7 A framework diagram of an optimized scheduling system for sewage treatment is disclosed.

[0050] Figure 8 A structural schematic diagram of an electronic device is disclosed. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0052] The following is combined with Figure 1-8 The preferred embodiments of the present invention are described in detail.

[0053] See attached Figure 1 The present invention proposes an optimization scheduling method for a digital twin model of energy consumption in a sewage treatment plant. The method takes the sewage treatment plant as the research object and constructs an optimization scheduling method under the background of the power market. The method fully utilizes the flexibility of energy consumption in the sewage treatment plant to achieve the purpose of reducing costs and increasing efficiency.

[0054] The optimization scheduling method of the digital twin model of the sewage treatment plant includes the following steps:

[0055] S1. Pre-treat the sewage treatment system and build the process flow structure of the sewage treatment plant

[0056] For example, Figure 2 Demonstrate a main process of sewage treatment, first pre-treat the sewage treatment system in the sewage treatment plant, and then build the process flow architecture of the sewage treatment plant. The sewage treatment system treats sewage around the flow of sewage and is equipped with a sludge treatment system.

[0057] S101. Pre-treatment of sewage treatment system

[0058] According to the actual process flow and relevant operating data, screen and classify the devices with regulation capabilities and high-energy-consuming equipment in the sewage treatment system.

[0059] S102. Build the process architecture of the sewage treatment plant

[0060] Screening of devices with regulation capabilities in sewage treatment systems. For example, the process flow architecture mainly includes the following equipment:

[0061] Coarse screen and lift pump room: used to remove larger suspended solids and particles in sewage, and then lift the sewage to subsequent treatment links through lift pumps;

[0062] Fine screen and grit chamber: used to remove smaller suspended solids and inorganic sand particles in sewage;

[0063] Hydrolysis acidification regulating tank: Use anaerobic microorganisms to decompose some complex organic matter in sewage into simple organic matter;

[0064] Inverted A 2 O Biochemical pool: used to remove organic matter, nitrogen, phosphorus and other pollutants in sewage;

[0065] Secondary sedimentation tank: The activated sludge (MLVSS) and water in the mixed liquor after biochemical treatment are separated by gravity sedimentation, and the clarified water flows into the subsequent treatment link;

[0066] Fiber disc filter cloth filter: further removes suspended matter and colloidal substances in clarified water;

[0067] Ultraviolet disinfection channel: Use ultraviolet rays to kill pathogenic microorganisms in sewage;

[0068] Tailwater lift pump room: The treated clean water is lifted to the discharge pipe for discharge.

[0069] S103. Analyze the electrical equipment required to build the process architecture

[0070] Obtain the historical electricity consumption data of the sewage treatment system and calculate the electricity consumption proportion EUP of each electrical equipment in the sewage treatment system v , the specific formula is as follows:

[0071]

[0072] Among them, EU v represents the annual power consumption of the vth electrical equipment;

[0073] Furthermore, the conditions for setting the electrical equipment to construct the process flow architecture need to satisfy the following formula: EUP v ≥θ, then the electrical equipment is used as an alternative modeling equipment;

[0074] Among them, θ is the minimum electricity consumption ratio of the electrical equipment required to build the process flow architecture.

[0075] S104. Analyze the adjustable power consumption of alternative modeling equipment

[0076] According to the candidate modeling devices selected in step S101, the adjustable capacity of the power consumption of these candidate modeling devices is analyzed.

[0077] Exemplarily, the electrically adjustable devices in the sewage treatment system mainly include lift pumps and aeration fans, and their electrically adjustable capabilities are achieved through variable frequency speed regulation; the electrically adjustable devices in the sewage treatment system also include underwater flowmakers, and their electrically adjustable capabilities are achieved by controlling the number of enabled devices.

[0078] Among them, the coarse screen and lift pump room and the tailwater lift pump room both include lift pumps; the fine screen and grit chamber, hydrolysis acidification regulating tank, inverted A 2 O Biochemical tank, secondary sedimentation tank, fiber disc filter cloth filter tank all contain underwater flow generators; refer to the attached Figure 2 The "aeration" in the formula stands for aeration fan.

[0079] S105. Analyze the energy storage device in the sewage treatment system

[0080] In the sewage treatment system, the water reservoirs in different treatment links serve as important energy storage devices, which can adjust the amount of water treated at different time periods. The adjustment of the amount of water treated at different time periods is achieved by dispatching the water amount of the water reservoirs in different treatment links.

[0081] S106. Establish energy model framework for sewage treatment plants

[0082] According to the analysis results of steps S101-S103, the architecture of the digital twin model of energy consumption of the sewage treatment plant is constructed;

[0083] For example, the architecture of the digital twin model of wastewater treatment plant energy consumption is as follows: Figure 3 As shown, in accordance with the order of sewage treatment, it includes an inlet tank, a pretreatment lift pump, a hydrolysis acidification tank, a hydrolysis acidification equipment, a biochemical treatment tank, a biochemical treatment equipment, an aeration fan, a filter tank, a filter disinfection equipment, a tailwater tank, and a tailwater lift pump.

[0084] S2. Build a digital twin model of energy consumption in sewage treatment plants

[0085] Based on the architecture of the energy consumption digital twin model of the sewage treatment plant established in step S104, the energy consumption digital twin model of each sewage treatment link is constructed, specifically including:

[0086] S201, water inlet pool

[0087] 1. The water storage state constraint of the water inlet pool satisfies the following formula:

[0088]

[0089] in, It indicates the predicted amount of sewage injected into the sewage treatment system on the next day; Indicates the outflow rate of the water inlet pool (extracted by the pretreatment lift pump); Indicates the maximum storage water volume of the water inlet pool; Indicates the initial storage water volume in the water inlet tank; represents the amount of stored water in the water inlet pool during period t;

[0090] Lim 1,up The upper limit of the amount of water allowed to be stored in the water inlet pool; Lim 1,down is the lower limit of the amount of water allowed to be stored in the water inlet pool; Δt1 is the length of the time period. If one hour is the length of a time period, the whole day can be divided into 24 time periods. max =24.

[0091] 2. The water volume required for the whole day must meet the following formula:

[0092]

[0093] Among them, Q req represents the minimum amount of sewage treatment required for the day, and formula (3) represents the total amount of sewage flowing out of the inlet pool during all periods of the day. Must be greater than or equal to the minimum amount of sewage treatment required for the day Q req .

[0094] For example, it is stipulated that all the sewage flowing in must be treated on the day, satisfying the following formula:

[0095]

[0096] S202, pretreatment boost pump

[0097] The pretreatment boost pump is a variable frequency speed regulation device, and the power of the pretreatment boost pump is adjusted by adjusting its frequency.

[0098] 1. The minimum and maximum flow constraints corresponding to the frequency satisfy the following formula:

[0099]

[0100] in, represents the water flow rate pumped out by the i-th pretreatment lift pump; Indicates the start / stop status of the i-th pretreatment lift pump in period t, which is a 0-1 variable; represents the pumping flow rate of the i-th pretreatment lift pump corresponding to the minimum allowed frequency; represents the pumping flow rate of the i-th pretreatment lift pump corresponding to the maximum allowable frequency;

[0101] Flow rate out of the water pool It is the total water flow rate pumped out by the pretreatment lift pump Satisfies the following formula:

[0102]

[0103] 2. Adjust rate constraints

[0104] In the variable frequency speed regulation mode of the pretreatment boost pump, the adjustment rate of the pumping flow of the i-th pretreatment boost pump needs to meet the upper and lower limit requirements and satisfy the following formula:

[0105]

[0106] in, The upper limit of the adjustment rate of the pretreatment lift pump; It is the lower limit of the regulation rate of the pretreatment boost pump.

[0107] 3. Pre-treatment boost pump power consumption

[0108] Since the pretreatment boost pump is variable frequency speed controlled, the power consumption of the pretreatment boost pump is With its pumping flow, it satisfies the following formula:

[0109]

[0110]

[0111] in, is the power consumption of all pretreatment boost pumps during period t; is the rated pumping flow of the i-th pretreatment lift pump; is the rated power consumption of the i-th pretreatment boost pump.

[0112] S203, hydrolysis acidification tank

[0113] 1. The water intake constraint satisfies the following formula:

[0114]

[0115] in, is the water inflow into the hydrolysis acidification tank, that is, the amount of water pumped out by the pretreatment lift pump.

[0116] 2. Outflow constraint, satisfying the following formula:

[0117] The outflow of the hydrolysis acidification tank is determined by underwater flow devices such as flow generators and satisfies the following formula:

[0118]

[0119] in, is the start / stop status of the kth flow-pushing device in the hydrolysis acidification tank during period t, that is, a 0-1 variable; is the rated water flow rate of the kth plug flow device in the hydrolysis acidification tank.

[0120] 3. The water storage state constraint of the hydrolysis acidification tank satisfies the following formula:

[0121]

[0122] in, Indicates the maximum storage water volume of the hydrolysis acidification tank; Lim 2,up Indicates the upper limit of the amount of water allowed to be stored in the hydrolysis acidification pool; Lim 2,down Indicates the lower limit of the amount of water allowed to be stored in the hydrolysis acidification pool;

[0123] is the amount of water stored in the hydrolysis acidification tank during period t; is the initial storage water volume in the hydrolysis acidification tank; is the outflow rate of the hydrolysis acidification tank; Δt2 is the length of the time period. If one hour is the length of a time period, the whole day can be divided into 24 time periods. max =24.

[0124] 4. The water volume required for the whole day must meet the following formula:

[0125]

[0126] in, is the outflow rate of the hydrolysis acidification tank; Q req The minimum amount of sewage to be treated on that day.

[0127] 5. Hydraulic retention time constraints

[0128] For sewage treatment tanks such as hydrolysis acidification tanks that involve chemical reactions, sufficient reaction time needs to be reserved to satisfy the following formula:

[0129]

[0130] in, It is the minimum hydraulic retention time requirement for the hydrolysis acidification tank.

[0131] 6. Electricity consumption of hydrolysis acidification tank

[0132] The electricity consumption of the hydrolysis acidification tank is mainly for underwater flow equipment, which satisfies the following formula:

[0133]

[0134] in, is the power consumption of the kth underwater flow-pushing device in the hydrolysis acidification tank during period t; The power consumption of all underwater flow-pushing equipment in the hydrolysis acidification tank during period t; is the rated power consumption of the kth underwater flow equipment in the hydrolysis acidification tank.

[0135] S204, biochemical treatment pool

[0136] 1. The water intake constraint satisfies the following formula:

[0137]

[0138] in, It indicates the water inflow into the biochemical treatment pool, which is the amount of water discharged from the hydrolysis acidification pool.

[0139] 2. Outflow constraint, satisfying the following formula:

[0140]

[0141] in, Indicates the start / stop status of the kth flow-pushing device in the biochemical treatment pool during period t, i.e., a 0-1 variable; is the rated water flow rate of the kth flow-pushing device in the biochemical treatment pool; The amount of water discharged from the biochemical treatment pool.

[0142] 3. Water storage state constraints satisfy the following formula:

[0143]

[0144] in, Indicates the maximum storage water volume of the biochemical treatment pool; Lim 3,down The lower limit of the amount of water allowed to be stored in the biochemical treatment pool; Lim 3,up The upper limit of the amount of water allowed to be stored in the biochemical treatment pool;

[0145] is the amount of water stored in the biochemical treatment pool during period t; is the initial storage water volume in the biochemical treatment pool; Δt3 is the time period length. If 1 hour is the length of a time period, the whole day can be divided into 24 time periods. max =24.

[0146] 4. The water volume required for the whole day must meet the following formula:

[0147]

[0148] 5. Hydraulic retention time constraint satisfies the following formula:

[0149]

[0150] in, It is the minimum hydraulic retention time requirement for the biochemical treatment pool.

[0151] 6. Power consumption of biochemical treatment pool

[0152] The outflow of the biochemical treatment pool is determined by underwater flow devices such as flow generators, and satisfies the following formula:

[0153]

[0154] in, is the rated power of the underwater flow-pushing equipment k; is the power consumption of a single underwater flow-pushing device in the biochemical treatment pool during period t; It is the power consumption of all underwater flow devices in the biochemical treatment pool during period t.

[0155] S205, aeration fan

[0156] The aeration fan is similar to the pretreatment lift pump, both of which are variable frequency speed regulation devices.

[0157] 1. The minimum and maximum air volume constraints corresponding to the frequency satisfy the following formula:

[0158]

[0159] in, represents the air supply of the jth aeration fan; Indicates the start / stop status of the jth aeration fan in period t, which is a 0-1 variable; is the air supply volume of the jth aeration fan corresponding to the minimum allowed frequency; is the air supply volume of the jth aeration fan corresponding to the maximum allowable frequency.

[0160] The total air supply of all aeration fans satisfies the following formula:

[0161]

[0162] 2. Adjust rate constraints

[0163] When the aeration fan is in variable frequency speed regulation mode, the adjustment rate of the flow rate handled by the jth aeration fan needs to meet the upper and lower limit requirements and satisfy the following formula:

[0164]

[0165] in, Indicates the upper limit of the aeration fan's adjustment rate; Indicates the lower limit of the aeration fan regulation rate.

[0166] 3. Air supply volume constraints

[0167] The relevant chemical reactions in the biochemical treatment pool require sufficient oxygen supply. The air demand is calculated based on the oxygen demand; the minimum oxygen demand Satisfies the following formula:

[0168]

[0169] in, Indicates the water inflow of the biochemical treatment pool; the value range of a is 0.42~0.53, and the unit is kg O2 / kgBOD5 (this unit is equivalent to the amount of oxygen required to remove 1kg BOD5); L r Indicates the weight of BOD5 removed from unit volume of sewage, in kg BOD5 / m 3 ;

[0170] BOD5 represents pollutants; V is the volume of the aeration tank in m 3 ; The biochemical treatment pool includes: an anaerobic pool, an anoxic pool, and an aerobic pool; the aerobic pool needs oxygen, which is the corresponding aeration pool; b represents the oxygen demand rate of sludge self-oxidation, the unit is kg O2 / (kg MLVSS·d), generally 0.11 to 0.19;

[0171] N WV is the concentration of volatile suspended solids in sewage (MLVSS), in kg / m 3 .

[0172] according to Combined with formula (1), further transformation:

[0173]

[0174] Among them, F W Indicates sludge load, unit is kg BOD5 / (kg MLVSS·d).

[0175] The actual oxygen delivery (oxygen transfer rate) is converted into the standard oxygen transfer rate to satisfy the following formula:

[0176]

[0177] in, is the corresponding actual oxygen delivery (under minimum oxygen delivery conditions) The standard oxygen transfer rate of sm is the average dissolved oxygen (DO) value of clean water; C s is the saturated dissolved oxygen (DO) value in clean water under standard conditions, which is equal to 9.17 mg / L; C0 is the residual dissolved oxygen (DO) value of the mixed solution, which is generally 2 mg / L; T is the temperature of the mixed solution, which is generally 5-30°C;

[0178] α is the ratio of the total oxygen transfer coefficient of the mixed liquid to that of the clean water, which is generally 0.8 to 0.85; β is the ratio of the saturated dissolved oxygen of the mixed liquid to that of the clean water, which is generally 0.9 to 0.97.

[0179] The aeration fan needs to adjust the air supply demand according to the oxygen concentration to meet the following formula:

[0180]

[0181] in, Indicates the air supply demand during period t; E A Indicates the oxygen conversion efficiency.

[0182] 4. Wind pressure constraints

[0183] The aeration fan uses an underwater microporous aeration head to supply air. As the water depth increases, the wind pressure requirement also increases, satisfying the following formula:

[0184]

[0185] in, Indicates the minimum wind pressure requirement value during period t; h water Indicates the water depth of the biochemical treatment pool; It represents the amount of water stored in the biochemical treatment pool during period t; Represents the cross-sectional area of ​​the biochemical treatment pool.

[0186] The aeration fan adopts variable frequency speed regulation. The air pressure and air volume of the aeration fan satisfy the following formula:

[0187]

[0188] in, is the minimum wind pressure requirement value of the jth fan in period t, and equal; is the rated wind pressure of the jth fan; is the minimum air supply value corresponding to the minimum wind pressure value in period t; is the rated air supply volume.

[0189] The air volume requirement is derived based on the air pressure requirement of the aeration fan. Combined with formulas (32)-(35), the following formula is calculated:

[0190]

[0191] 5. Power consumption of aeration fan

[0192] The aeration fan adopts variable frequency speed regulation. The power consumption of the aeration fan is The following formula is satisfied between the air supply volume and the air supply volume:

[0193]

[0194] in, is the power consumption of all aeration fans during period t; is the rated air delivery volume of the jth aeration fan in period t; is the rated power consumption of the j-th aeration fan in period t.

[0195] S206, filtration pool

[0196] 1. The water intake constraint satisfies the following formula:

[0197]

[0198] in, It indicates the amount of water entering the filter tank, which is the amount of water discharged from the biochemical treatment tank.

[0199] 2. Outflow constraint, satisfying the following formula:

[0200]

[0201] in, Indicates the start / stop status of the kth flow-pushing device in the filter pool during period t, which is a 0-1 variable; represents the rated water flow rate of the kth flow-pushing device in the filter tank; Indicates the outflow from the filter pool.

[0202] 3. Water storage state constraints satisfy the following formula:

[0203]

[0204] in, represents the amount of water stored in the filter tank during period t; Indicates the initial storage water volume in the filter tank; Indicates the maximum storage water volume of the filter pool; Lim 4,down Indicates the lower limit of the amount of water that can be stored in the filter pool;

[0205] Lim 4,up is the upper limit of the amount of water allowed to be stored in the filter pool; Δt4 is the length of the time period. If one hour is the length of a time period, the whole day can be divided into 24 time periods. max =24.

[0206] 4. The water volume required for the whole day must meet the following formula:

[0207]

[0208] Among them, Q reqThe minimum amount of sewage to be treated on that day.

[0209] 5. Power consumption of filter pool

[0210] The electricity consumption of the filter pool is mainly for underwater flow equipment, which satisfies the following formula:

[0211]

[0212] in, is the power consumption of a single underwater flow-pushing device in the biochemical treatment pool during period t; is the power consumption of all underwater flow-pushing equipment in the biochemical treatment pool during period t; is the rated power consumption of the underwater flow equipment k in the biochemical treatment pool.

[0213] S207, tailwater pool

[0214] 1. The water intake constraint satisfies the following formula:

[0215]

[0216] in, The water inflow of the tailwater pool is the amount of water flowing out of the filter pool.

[0217] 2. Water storage state constraints satisfy the following formula:

[0218]

[0219] in, is the amount of water stored in the filter pool during period t; is the outflow rate of the tailwater pool (extracted by the tailwater lift pump); is the initial storage water volume in the filter tank; Lim 5,down Indicates the lower limit of the amount of water that can be stored in the filter pool. 5,up Indicates the upper limit of the amount of water that can be stored in the filter pool;

[0220] Indicates the maximum storage water volume of the filter pool; Δt5 is the time period length. If 1 hour is the length of a time period, the whole day can be divided into 24 time periods. max =24.

[0221] S208, tailwater lift pump

[0222] The tailwater lift pump is a variable frequency speed regulation device, and the adjustment of the tailwater lift pump power is achieved by adjusting its frequency.

[0223] 1. The minimum and maximum flow constraints corresponding to the frequency satisfy the following formula:

[0224]

[0225] in, is the start / stop status of the i-th tailwater lift pump in period t, that is, a 0-1 variable; is the water flow rate pumped out by the i-th tailwater lift pump; represents the pumping flow rate of the i-th tailwater lift pump corresponding to the minimum allowable frequency; It represents the pumping flow rate of the i-th tailwater lift pump corresponding to the maximum allowable frequency.

[0226] Total water flow rate pumped out by all tailwater lift pumps Satisfies the following formula:

[0227]

[0228] 2. Adjust rate constraints

[0229] When the tailwater lift pump is in variable frequency speed regulation mode, the adjustment rate of the processing flow rate needs to meet the upper and lower limit requirements and satisfy the following formula:

[0230]

[0231] in, Indicates the upper limit of the regulation rate of the tailwater lift pump; Indicates the lower limit of the regulation rate of the tailwater lift pump.

[0232] 3. Power consumption of tailwater lifting pump

[0233] The tailwater lifting pump is a variable frequency speed regulating device. The power consumption of the tailwater lifting pump is The pumping flow rate satisfies the following formula:

[0234]

[0235] in, is the power consumption of all tailwater lift pumps during period t; is the rated pumping flow rate of the i-th tailwater lift pump; is the rated power consumption of the i-th tailwater lift pump.

[0236] S209, other electrical equipment not included in the optimization

[0237] Hydrolysis acidification equipment, biochemical treatment equipment, and filter disinfection equipment are considered to be equipment with only start-stop functions. It can be seen that the power consumption of equipment with only start-stop functions remains at rated power and satisfies the following formula:

[0238]

[0239] in, Respectively represent the power consumption of hydrolysis acidification equipment, biochemical treatment equipment and filter disinfection equipment during time period t; Respectively represent the rated power consumption of hydrolysis acidification equipment, biochemical treatment equipment and filter disinfection equipment;

[0240] They represent the start and stop status of the hydrolysis acidification equipment, biochemical treatment equipment, and filter disinfection equipment during period t, respectively, and are known 0-1 variables. Since the equipment with only start and stop functions has poor adjustability, such equipment is not considered in the optimal scheduling.

[0241] S210. Combining relevant formulas (2)-(52), a digital twin model of energy consumption of the sewage treatment plant is constructed.

[0242] S3. Constructing a day-ahead optimal dispatching model for sewage treatment plants under the power market environment

[0243] Based on the digital twin model of sewage treatment plant energy consumption, considering the power market background and combining with the power demand response market, a day-ahead optimal scheduling model of sewage treatment plants under the power market background is constructed.

[0244] The objective function of the optimization scheduling method is cost minimization, which satisfies the following formula:

[0245]

[0246] Where C represents the operating cost (mainly electricity charges); R represents the income from participating in the electricity demand response market; p t The predicted time-of-use electricity price in the electricity market; is the predicted subsidy price of the electricity demand response market; base,t Represents the operational baseline of the wastewater treatment plant; is the total power consumption of the optimized part (adjustable part) of the sewage treatment plant, Δt is the time period length. If 1 hour is the length of a time period, the whole day can be divided into 24 time periods, T max =24, which satisfies the following formula:

[0247]

[0248] Therefore, the objective function satisfies the following formula:

[0249]

[0250] According to the above objective function, a day-ahead optimal scheduling model for sewage treatment plants in the electricity market environment is constructed.

[0251] Example

[0252] With reference to the actual data of a sewage treatment plant, the implementation method of the above-mentioned sewage treatment plant's day-ahead optimization scheduling model is described with one hour as one time period.

[0253] Step 1: Predict data

[0254] 1. Flow rate of sewage to be treated The specific table is as follows:

[0255] Time <![CDATA[Wastewater volume (m 3 / h)]]> Time <![CDATA[Wastewater volume (m 3 / h)]]> 1 800 13 1000 2 700 14 1000 3 900 15 1500 4 1000 16 1400 5 1000 17 1200 6 1100 18 1100 7 1200 19 1000 8 1300 20 1000 9 1200 21 1100 10 1500 22 800 11 1000 23 700 12 900 24 600

[0256] 2. Time-of-use electricity price in the power market (p t ) and demand response prices The specific table is as follows:

[0257]

[0258] 3. Run baseline (P base,t ), as shown in the following table:

[0259] Time Electricity power baseline (kW) Time Electricity power baseline (kW) 1 487.6 13 487.6 2 487.6 14 487.6 3 487.6 15 487.6 4 487.6 16 487.6 5 487.6 17 487.6 6 487.6 18 487.6 7 487.6 19 487.6 8 487.6 20 487.6 9 487.6 21 487.6 10 487.6 22 487.6 11 487.6 23 487.6 12 487.6 24 487.6

[0260] Step 2: Known Data

[0261] 1. Pretreatment boost pump

[0262] 2 pre-treatment booster pumps, rated power 75kW each, rated flow 800m 3 / h;

[0263] The pretreatment lift pump pumping flow corresponding to the maximum allowable frequency and the minimum allowable frequency satisfies the following equation:

[0264] Adjust the rate to satisfy the following equation:

[0265] 2. Tailwater lifting pump

[0266] 1 tailwater lift pump, rated power 110kW, rated flow 1600m 3 / h;

[0267] The tailwater lift pump flow rate corresponding to the maximum allowable frequency and the minimum allowable frequency satisfies the following equation:

[0268] Adjust the rate to satisfy the following equation:

[0269] 3. Reservoir

[0270] In the sewage treatment system, the water reservoirs in different treatment links serve as important energy storage devices, which can adjust the amount of water treated at different time periods. The adjustment of the amount of water treated at different time periods is achieved by dispatching the water amount of the water reservoirs in different treatment links.

[0271] The maximum water storage capacity of the pool satisfies the following equation: Percentage of the upper limit of water storage allowed: Lim 1,up =Lim 2,up =Lim 3,up =Lim 4,up =Lim 5,up =1; Initial water storage capacity:

[0272] The water storage tank includes water inlet tank, hydrolysis acidification tank, biochemical treatment tank and other water tanks, which are represented in sequence by the superscripts 1, 2, 3, 4, and 5 of the symbols as hydrolysis acidification regulating tank, water inlet tank, hydrolysis acidification tank, biochemical treatment tank, filtration tank, and tailwater tank.

[0273] Percentage of lower limit of water storage allowed: Lim 1,down =Lim 2,down =Lim 3,down =Lim 4,down =Lim 5,down =0; hydraulic retention time satisfies the following equation:

[0274] The hydrolysis acidification tank, biochemical treatment tank and filtration tank are equipped with 4 underwater flow-pushing devices, each with a rated treatment flow of 400m 3 / h, rated power 20kW.

[0275] 4. Aeration fan

[0276] 1 aeration fan, rated power Rated air flow Rated wind pressure The upper and lower limits of the adjustment rate satisfy the following equation:

[0277] Oxygen demand rate of sludge self-oxidation: b = 0.16kg O2 / (kg MLVSS·d); cross-sectional area of ​​biochemical treatment tank Oxygen conversion rate E A =0.1; average dissolved oxygen (DO) value of clean water C sm =9.038mg / L; F W =0.4kg BOD5 / (kg MLVSS·d);

[0278] The residual dissolved oxygen (DO) value of the mixed solution is C0 = 2 mg / L; the ratio of saturated dissolved oxygen of the mixed solution to that of clean water is β = 0.9; the K L The ratio of a value is α = 0.8; the concentration of BOD5 removed is L r =0.18kg / m 3 ; a = 0.5kg O2 / kg BOD5.

[0279] The results of the embodiment are analyzed in detail. Figure 4-6 , the change of water volume in the water inlet pool shows that, referring to the demand response period, for example: 6, 7, 12, 13, the outflow of the water inlet pool is reduced to 0, and the water storage capacity of the water inlet pool continues to increase, achieving a reduction in electricity consumption, thereby obtaining corresponding subsidies.

[0280] When making an operation plan with the goal of minimizing costs, try to avoid using electricity during periods of high electricity prices and try to concentrate electricity use during periods of low electricity prices. Due to the constraints of the full-day processing flow and the inflow flow conditions specified in formula (3), even if the water storage capacity of the water inlet pool is sufficient, all electricity consumption cannot be allocated to the period of low electricity prices.

[0281] Refer to the attached Figure 5 , because the inlet pool has formulated the optimal water discharge plan according to the time-of-use electricity price and demand response subsidy, that is, to reduce electricity consumption during the demand response period and try to use electricity during the low electricity price period. For the subsequent pool, the outflow of the previous pool is the inflow of the pool, and the subsequent pools (hydrolysis acidification pool, biochemical treatment pool, filtration pool, tailwater pool) are consistent with the optimal period of the inlet pool flow;

[0282] When the operation plan is formulated with the goal of minimizing costs, the optimal operation plan for the subsequent water pool is to discharge the water immediately during the water inflow period of the water pool, and the water volume changes in the subsequent water pools (hydrolysis acidification pool, biochemical treatment pool, filtration pool, tailwater pool) are the same.

[0283] Refer to the attached Figure 6 , the actual distribution of the power consumption of the equipment in each link is consistent with the actual distribution of the outflow flow of the corresponding pool;

[0284] Among them, the power consumption of aeration fans is constrained by wind pressure, air supply volume, etc., and the actual distribution of power consumption of aeration fans varies.

[0285] The total cost of the operation plan formulated using the optimized scheduling method of the present invention (approximately RMB 4,149.97 after considering the demand response subsidy) decreased by approximately 26.25% compared to the total cost under the baseline operation mode (5,626.88 yuan).

[0286] See attached Figure 7The present invention also proposes an optimization scheduling system for a digital twin model of energy consumption of a sewage treatment plant, which includes a construction module of a process flow architecture of a sewage treatment plant, a construction module of a digital twin model of energy consumption of a sewage treatment plant, and a construction module of a day-ahead optimization scheduling method of a sewage treatment plant.

[0287] The building module of the process flow architecture of the sewage treatment plant is used to build the process flow architecture of the sewage treatment plant by pre-treating the sewage treatment system;

[0288] The construction module of the digital twin model of energy consumption of sewage treatment plants is used to construct the digital twin model of energy consumption of each sewage treatment link according to the process flow architecture of the sewage treatment plant;

[0289] The construction module of the sewage treatment plant day-ahead optimal scheduling method is used to consider the power market background and combine it with the power demand response market to construct a day-ahead optimal scheduling model for sewage treatment plants under the power market background.

[0290] The modules described above may be implemented in whole or in part through software, hardware, or a combination thereof, supporting processors embedded in or independent of a computer device in hardware form, and also supporting memories stored in a computer device in software form, so that the processor can call and execute operations corresponding to the modules described above.

[0291] An embodiment of the present invention provides a computer storage medium, which stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor so that the at least one processor can execute a computer program for an optimization scheduling method of a digital twin model of energy consumption of a sewage treatment plant as described above.

[0292] The storage medium includes, for example, a USB flash drive, a mobile hard disk, a magnetic disk, a read-only memory (ROM), a random access memory (RAM), or an optical disk, and other media that can store program codes.

[0293] The embodiment of the present invention provides a device, see the attached Figure 8 , used to execute the above-mentioned coding management platform, the computer device includes a processor, a memory, a network interface and a database connected through a system bus. The processor of the computer device is used to provide computing and control capabilities; the memory of the computer device includes a non-volatile storage medium and an internal memory; the processor of the computer device implements the steps of the above-mentioned coding management method when executing the computer program; the non-volatile storage medium stores an operating system, a computer program and a database; the internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium.

[0294] It should be noted that the user information (including but not limited to user device information and personal information, etc.) and data (including but not limited to data used for analysis, stored data and displayed data, etc.) involved in the present invention are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0295] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention is described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. An optimization scheduling method for a digital twin model of energy consumption in a sewage treatment plant, characterized in that: The method comprises: Pre-treat the sewage treatment system and build the process flow structure of the sewage treatment plant; According to the process architecture of the sewage treatment plant, a digital twin model of energy consumption in each sewage treatment link is constructed; Considering the power market background and combining with the power demand response market, a day-ahead optimal dispatch model of the sewage treatment plant under the power market background is constructed; According to the day-ahead optimal dispatching model of sewage treatment plants under the background of electricity market, the optimal dispatching method of the digital twin model of energy consumption of sewage treatment plants is analyzed.

2. The method for optimizing the scheduling of a digital twin model of energy consumption in a sewage treatment plant according to claim 1 is characterized in that: The process flow architecture of constructing a sewage treatment plant includes the following steps: Analyze the alternative modeling equipment needed to build the process flow architecture; According to the selected candidate modeling equipment, analyzing the adjustable capacity of the power consumption of these candidate modeling equipment; Analyze energy storage devices in sewage treatment systems; Construct the architecture of the digital twin model of energy consumption of the sewage treatment plant.

3. The optimization scheduling method of the digital twin model of energy consumption of a sewage treatment plant according to claim 2 is characterized by: The electrical equipment required for analyzing and constructing the process flow architecture specifically includes: Obtain the historical electricity consumption data of the sewage treatment system and calculate the electricity consumption proportion EUP of each electrical equipment in the sewage treatment system v ; Set the conditions for the electrical equipment to build the process flow architecture to meet EUP v ≥θ, then the electrical equipment is used as an alternative modeling equipment; Among them, θ is the minimum electricity consumption ratio of the electrical equipment required to build the process flow architecture.

4. The optimization scheduling method of the digital twin model of energy consumption of a sewage treatment plant according to claim 1 is characterized by: The process flow structure of the sewage treatment plant includes: Pretreatment lifting pump, hydrolysis acidification tank, hydrolysis acidification equipment, biochemical treatment tank, biochemical treatment equipment, aeration fan, filter tank, filter disinfection equipment, tailwater tank, tailwater lifting pump, water inlet tank.

5. The method for optimizing the scheduling of a digital twin model of energy consumption in a sewage treatment plant according to claim 4 is characterized in that: The pretreatment boost pump is a variable frequency speed regulation device. The power consumption of the pretreatment boost pump and its own pumping flow rate satisfy the following formula: in, is the power consumption of all pretreatment boost pumps during period t; is the rated pumping flow of the i-th pretreatment lift pump; is the rated power consumption of the i-th pretreatment boost pump; represents the power consumption of the i-th pretreatment boost pump; Represents the water flow rate pumped out by the i-th pretreatment lift pump.

6. The method for optimizing the scheduling of a digital twin model of energy consumption in a sewage treatment plant according to claim 4 is characterized in that: The aeration fan is a variable frequency speed regulating device. The power consumption of the aeration fan and its air supply volume satisfy the following formula: in, is the power consumption of all aeration fans during period t; is the rated air delivery volume of the jth aeration fan in period t; is the rated power consumption of the jth aeration fan in period t; Represents the air supply of the i-th aeration fan.

7. The method for optimizing the scheduling of a digital twin model of energy consumption in a sewage treatment plant according to claim 1, characterized in that: The above construction obtains the day-ahead optimal dispatch model of the sewage treatment plant under the background of the power market. The objective function of the optimal dispatch method is to minimize the operating cost, which satisfies the following formula: Where C is the operating cost; R is the income from participating in the electricity demand response market; p t The predicted time-of-use electricity price in the electricity market; represents the forecasted subsidy price for the electricity demand response market; It represents the total electricity consumption of the adjustable part of the sewage treatment plant; P base,t represents the operating baseline of the sewage treatment plant; Δt is the time period length, T max The number of time periods throughout the day.

8. An optimization scheduling system for a digital twin model of energy consumption in a sewage treatment plant, characterized in that: The system includes a construction module for the process architecture of a sewage treatment plant, a construction module for the digital twin model of the sewage treatment plant's energy consumption, and a construction module for the day-ahead optimization scheduling method of the sewage treatment plant; The construction module of the process flow architecture of the sewage treatment plant is used to pre-treat the sewage treatment system and construct the process flow architecture of the sewage treatment plant; The construction module of the digital twin model of energy consumption of sewage treatment plants is used to construct the digital twin model of energy consumption of each sewage treatment link according to the process flow architecture of the sewage treatment plant; The construction module of the sewage treatment plant day-ahead optimal scheduling method is used to consider the power market background and combine it with the power demand response market to construct a day-ahead optimal scheduling model for sewage treatment plants under the power market background.

9. A computer storage medium, characterized in that One or more programs are stored. When the one or more programs are executed, the optimization scheduling method of the digital twin model of energy consumption of a sewage treatment plant as described in any one of claims 1 to 7 can be implemented.

10. A device, characterized in that: The system comprises a processor, a communication interface, a memory and a communication bus; the memory stores at least one program in a computer storage medium as claimed in claim 9 which can be loaded and executed by the processor.

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