Method and device for operating a polytropic coupled carnot cell water cycle energy system

Abstract

The application discloses a kind of operation optimization method and device of multi-energy coupling Carnot cell water circulation energy system, according to the temperature, flow of the equipment and water circulation loop of the Carnot cell water circulation energy system of multiple energy coupling such as electricity, cold, heat, domestic hot water etc., accurately control, obtain the optimal operation strategy set of the multi-energy coupling Carnot cell water circulation energy system;According to the optimal operation strategy set obtained, real-time control is carried out to the multi-energy coupling Carnot cell water circulation energy system.The working mechanism of each device of the system, the multi-energy coupling characteristics of water circulation process are modeled, the hourly multi-energy coupling dynamic mechanism between the multiple devices, multiple pipelines, multiple energy conversion of system supply-storage-demand is reflected, the hourly dynamic temperature and flow accurate optimization of Carnot cell water circulation energy system considering multi-energy coupling modeling and its operation control are realized, while improving the stability of system, reduce the operation cost of system.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of energy system optimization, and particularly relates to a running optimization method and device of a multi-energy coupling Carnot battery water circulation energy system. BACKGROUND

[0002] Renewable energy with intermittency and volatility accounts for a higher and higher proportion in global energy systems, which has caused a huge impact on the stability and reliability of energy systems. Carnot battery is a low-cost and region-unrestricted electricity-heat-electricity energy storage technology. The introduction of Carnot battery into a comprehensive energy system can effectively promote the consumption of renewable energy and smooth the fluctuation of renewable energy. Therefore, the optimization of Carnot battery water circulation energy system is particularly important.

[0003] At present, the design optimization and implementation of Carnot battery water circulation energy system mainly formulate rough charging and discharging and cooling and heating strategies according to different demand scenarios, which cannot depict the actual running mechanism characteristics of Carnot battery water circulation energy system, and meanwhile faces a series of problems such as randomness of demand-side electric, cooling and heating loads, stability and comfort of energy system cooling and heating temperature, multi-energy coupling between supply and demand, etc., which brings great challenges to the stable, reliable and economic operation of Carnot battery water circulation energy system. SUMMARY

[0004] The application provides a running optimization method and device of a multi-energy coupling Carnot battery water circulation energy system, which can effectively cope with load randomness, realize accurate regulation and control of Carnot battery water circulation energy system temperature and flow, and improve the overall operation efficiency and economy of Carnot battery water circulation energy system.

[0005] To achieve the above purpose, the multi-energy coupling Carnot battery water circulation energy system and the running optimization method thereof, comprising the following steps:

[0006] S1, collecting demand load samples, wherein the demand load samples include user electric demand, cooling demand, heating demand and domestic hot water demand in each period;

[0007] S2, optimizing the running of the multi-energy coupling Carnot battery water circulation energy system of electric, cooling, heating demand and domestic hot water according to the user demand data collected in S1, to obtain an optimal running strategy set of the multi-energy coupling Carnot battery water circulation energy system, specifically comprising the following steps:

[0008] S2.1, constructing a mathematical model of the multi-energy coupling Carnot battery water circulation energy system, wherein the mathematical model includes an objective function and constraint conditions, and the objective function minimizes the system running cost;

[0009] S2.2, constructing a sample parameter set, wherein the sample parameter set includes one device parameter sample and one system environment parameter sample;

[0010] S2.3, generating multiple scenario trees of uncertainty load based on demand load sample, performing scenario reduction to obtain final scenario tree;

[0011] S2.4, based on sample parameter set constructed in S2.2 and final scenario tree obtained in S2.3, solving mathematical model constructed in S201 to obtain optimal operation strategy set in system scheduling period;

[0012] S3, performing real-time control on the multi-energy coupling Carnot battery water cycle energy system according to the optimal operation strategy set obtained in S2.

[0013] Further, in S2.1, the constraint conditions include:

[0014] Operation constraint of water circulation sub-circuit of chiller:

[0015] Wherein, is the chiller operation power in the kth period under the s th scenario; is the chiller refrigeration efficiency in the kth period under the s th scenario; c W is the specific heat capacity of water, is the chiller water circulation pipeline switch state in the kth period under the s th scenario, m EC is the flow of chiller water circulation pipeline, is the chiller return water temperature in the kth period under the s th scenario, is the chiller outlet water temperature in the kth period under the s th scenario;

[0016] Operation constraint of water circulation sub-circuit of electric boiler:

[0017] Wherein, is the electric boiler operation power in the kth period under the s th scenario, η EB is the heating efficiency of electric boiler; is the electric boiler water circulation pipeline switch state in the kth period under the s th scenario, m EB is the flow of electric boiler water circulation pipeline, is the electric boiler outlet water temperature in the kth period under the s th scenario, is the electric boiler return water temperature in the kth period under the s th scenario;

[0018] The operation constraint of Carnot battery unit includes heat pump operation constraint, high-temperature heat storage tank operation constraint, low-temperature heat storage tank operation constraint and heat engine unit operation constraint;

[0019] Operation constraint of water circulation sub-circuit of absorption chiller:

[0020] wherein, η EX is the working efficiency of the heat exchanger, η AC is the refrigeration efficiency of the absorption chiller; is the absorption chiller water circulation pipe switch state in the kth time period under the st scenario, m AC is the flow rate of the absorption chiller water circulation pipe, is the absorption chiller outlet water temperature in the kth time period under the st scenario;

[0021] system operation constraints;

[0022]

[0023]

[0024]

[0025] wherein, represents that the power grid is in the state of buying electricity in the kth time period under the st scenario, and is 0 otherwise; represents that the power grid is in the state of selling electricity in the kth time period under the st scenario, and is 0 otherwise;d k,s is the terminal electric load in the kth time period under the st scenario, q k,s is the terminal cold load in the kth time period under the st scenario, g k,s is the terminal heat load in the kth time period under the st scenario.

[0026] Further, the heat pump operation constraint is:

[0027] wherein is the kth time period under the st scenario, η HP is the heating efficiency of the heat pump; is the hot water tank water circulation pipe state in the kth time period under the st scenario, represents that the hot water tank water circulation pipe is in the state of charging in the kth time period under the st scenario, and is 0 otherwise; m LT,HT is the water flow rate of the low-temperature thermal storage tank flowing to the high-temperature thermal storage tank, is the heat pump outlet water temperature in the kth time period under the st scenario, is the storage water temperature of the low-temperature thermal storage tank in the kth time period under the st scenario;

[0028] The high-temperature thermal storage tank operation constraint is

[0029]

[0030]

[0031]

[0032] wherein, represents the state of the water circulation pipeline of the hot water tank in the s-th scenario in the k-th period, and vice versa; is the water storage capacity of the high-temperature thermal storage tank in the s-th scenario in the k+1-th period, is the water storage capacity of the high-temperature thermal storage tank in the s-th scenario in the k-th period, m HT,LT is the water flow rate of the high-temperature thermal storage tank flowing to the low-temperature thermal storage tank; is the water storage temperature of the high-temperature thermal storage tank in the s-th scenario in the k-th period; and respectively represent the heat transferred by the high-temperature thermal storage tank to the heat exchanger cold water circulation loop and the hot water circulation loop, U HT is the unit area heat loss coefficient of the high-temperature thermal storage tank, A HT is the surface area of the high-temperature thermal storage tank, T ENV is the ambient temperature;

[0033] The operation constraints of the low-temperature thermal storage tank are:

[0034]

[0035]

[0036] wherein, is the water storage capacity of the low-temperature thermal storage tank in the s-th scenario in the k+1-th period, is the water storage capacity of the low-temperature thermal storage tank in the s-th scenario in the k-th period, U LT is the unit area heat loss coefficient of the low-temperature thermal storage tank, A LT is the surface area of the low-temperature thermal storage tank;

[0037] The operation constraints of the heat and power unit are:

[0038] wherein is the discharging power of the Carnot cell in the s-th scenario in the k-th period, η HE is the power generation efficiency of the heat and power unit.

[0039] Further, S2.3 includes the following steps:

[0040] S2.3.1, according to the collected user electricity demand, cold demand, heat demand and hot water demand data, S scenarios are generated according to the given standard deviation X respectively;

[0041] S2.3.2, the Euclidean distance of random variables between all scenarios is calculated;

[0042] S2.3.3, delete any one of the pair of scenarios with the minimum Euclidean distance, and add the probability of the deleted scenario to the scenario with the minimum Euclidean distance, and change the probability of the deleted scenario to zero;

[0043] S2.3.4, repeat the above steps Y times, wherein Y=(0.8-0.99)*S, and finally obtain the final scenario tree containing S-Y scenarios.

[0044] Further, in S2.4, the mathematical model constructed in S201 is solved by using a rolling optimization method to obtain the optimal operation strategy set in the system scheduling period.

[0045] Further, S2.4 includes the following steps:

[0046] S2.4.1, in each scenario, shorten the scheduling period time domain from [1, K] to [k, k+τ), and calculate the initial objective function J0 of the system according to the obtained device parameter samples and system environment parameter samples;

[0047] S2.4.2, in each scenario, solve the mathematical model established in S2.1 in the time domain [k, k+τ) to obtain the optimal operation strategy set, and the optimal operation strategy set of the time domain [k, k+τ) includes the optimal operation strategy of the k period, the k+1 period, the k+2 period, …, and the optimal operation strategy of the k period is taken as the system control set value of the k period;

[0048] S2.4.3, in each scenario, calculate the system objective function J1 and the optimal operation strategy set of the system in the time domain [k+1, k+1+τ), and only take the optimal operation strategy set of the k+1 period as the system control set value of the k+1 period;

[0049] S2.4.4, repeat S2.4.3, and the entire optimization interval rolls forward with time until the optimal operation strategy set of the time domain [K-τ, K] is calculated, and the optimal operation strategy set of the entire scheduling period [1, K] is obtained.

[0050] A multi-energy coupled Carnot battery water cycle energy system optimization device, comprising a perception analysis module, an optimization decision module, and a control scheduling module; the perception analysis module is used to collect the electricity, cooling, heating, and domestic hot water demand data of users, and transmit the data to the optimization decision module; the optimization decision module generates a final scenario tree of uncertain load according to the obtained demand data, and solves the model to obtain the optimal operation strategy set of the multi-energy coupled Carnot battery water cycle energy system, and transmits the optimal operation strategy set to the control scheduling module; the control scheduling module is used to control the key nodes such as the connection between each energy supply device and the pipeline, the connection between the energy storage device and the pipeline, the convergence of each branch pipeline, and the energy exchange of the end load.

[0051] Further, the optimization decision module comprises an initialization module, a sample construction module and a solving module; the initialization module is used for initializing the optimization decision module and determining the constraint condition and the objective function of the multi-energy coupled Carnot battery water cycle energy system, and constructing a mathematical model of the multi-energy coupled Carnot battery water cycle energy system; the sample construction module is used for constructing a sample parameter set, the sample parameter set comprising one device parameter sample and one system environment parameter sample; and the solving module is used for solving the constructed mathematical model and the sample parameter set by using a rolling optimization method to obtain an optimal operation strategy set in a system scheduling period.

[0052] Further, the optimization decision module comprises a data processing unit, a data storage unit and a data transmission unit; the data processing unit is used for supporting the multi-energy coupled Carnot battery water cycle energy system optimization device to execute the above-mentioned optimization method; the storage unit is used for storing the program code and data of the multi-energy coupled Carnot battery water cycle energy system optimization device; and the input and output unit realizes information interaction with the outside world.

[0053] Further, the optimization decision module comprises a processor, a bus and a memory; the processor is connected with the memory through the bus, is used for calling the computer program and data in the memory in real time through the bus, and executes the above-mentioned optimization method; and the memory is used for storing the computer program and data of the multi-energy water cycle system constant-temperature water supply optimization device.

[0054] Compared with the prior art, the multi-energy coupled Carnot battery water cycle energy system operation optimization method has at least the following beneficial technical effects: the multi-energy coupled Carnot battery water cycle energy system operation optimization method collects user electricity, cold and heat load demands to help accurately control the temperature and flow of each device and water circulation loop, optimizes the Carnot battery water cycle energy system considering multi-energy coupling and uncertainty, obtains an optimal operation strategy set of each device and energy supply key node in the multi-energy coupled Carnot battery water cycle energy system, and controls the multi-energy coupled Carnot battery water cycle energy system according to the obtained optimal operation strategy set.

[0055] Further, the present application not only considers the on-off state and operation power of the main devices in the multi-energy coupled Carnot battery water cycle energy system, but also models the working mechanism of each device, the multi-energy coupling characteristics of the water circulation process and the temperature and flow as the decision quantity, physically reflects the operation of each device and the key node of the pipeline and the working mechanism of the water supply and return to the end, focuses on depicting the temperature and flow operation of the key node of the water circulation system in the system, reflects the hour-level multi-energy coupling dynamic mechanism between the multi-device, multi-pipeline and multi-energy conversion of the system supply-storage-demand, and realizes the hour-level dynamic temperature and flow accurate optimization and operation control of the Carnot battery water cycle energy system considering multi-energy coupling modeling.

[0056] Furthermore, by employing scenario tree generation and reduction methods, typical scenarios that may be encountered during system operation are simulated to reduce the impact of demand uncertainty on system operation.

[0057] The optimization device proposed in this invention combines sensors and temperature and flow control devices to achieve intelligent control of the water-circulating Carnot battery water circulation energy system. It can achieve stable and coordinated supply of electricity, cold water, heat water, and domestic hot water at the terminal, effectively solve the impact of uncertain heat supply and load demand on the system in the multi-energy coupled Carnot battery water circulation energy system, deeply characterize and analyze the multi-energy coupling characteristics of the system, effectively coordinate the stable operation of the multi-energy coupled Carnot battery water circulation energy system, and reduce the system's operating costs while improving system stability. Attached Figure Description

[0058] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope.

[0059] In the attached diagram:

[0060] Figure 1 A schematic diagram of a multi-energy coupled Carnot battery water cycle energy system provided in a preferred embodiment of the present invention;

[0061] Figure 2 A flowchart of the operation optimization method for a multi-energy coupled Carnot battery water cycle energy system provided in a preferred embodiment of the present invention;

[0062] Figure 3 A schematic diagram of the optimized functional module of the multi-energy coupled Carnot battery water cycle energy system provided in a preferred embodiment of the present invention;

[0063] Figure 4 This is a schematic diagram of a first possible structure of the optimization decision module provided in a preferred embodiment of the present invention;

[0064] Figure 5 This is a schematic diagram of a second possible structure of the optimization decision module provided in a preferred embodiment of the present invention;

[0065] Figure 6 This is a schematic diagram of a third possible structure of the optimization decision module provided in a preferred embodiment of the present invention;

[0066] Appendix Figure 1 In the diagram, the thin solid line represents electricity, the thick solid line represents heat, and the thick dashed line represents cooling. Detailed Implementation

[0067] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. The components of the embodiments of the present application described in the drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0068] It should be noted that similar reference numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. Meanwhile, in the description of the present application, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance. As Figure 1 As shown in the figure, it is a system schematic diagram of a multi-energy coupled Carnot cell water circulation energy system. The multi-energy coupled Carnot cell water circulation energy system comprises photovoltaic power generation, a Carnot cell unit, a heat exchanger, an absorption chiller, an electric boiler, a water chiller and a water circulation pipeline loop.

[0069] The photovoltaic power generation is used to generate electricity for the system and the end electrical load.

[0070] The Carnot cell unit is used to consume the electricity generated by the photovoltaic power generation to generate heat and store it, and to release heat to generate electricity for the end electrical load during the load peak period. The Carnot cell unit comprises a heat pump, a heat engine unit, a high-temperature heat storage tank and a low-temperature heat storage tank, the water inlet of the heat pump is connected with the water outlet of the low-temperature heat storage tank, the water outlet of the heat pump is connected with the first water inlet of the high-temperature heat storage tank, the water inlet of the heat engine unit is connected with the first water outlet of the high-temperature heat storage tank, and the water outlet of the heat engine unit is connected with the water inlet of the low-temperature heat storage tank.

[0071] The heat exchanger is used for heat exchange between the high-temperature heat storage tank and the water circulation loop pipeline, the primary side water inlet of the heat exchanger is connected with the second water outlet of the high-temperature heat storage tank, the primary side water outlet of the heat exchanger is connected with the second water inlet of the high-temperature heat storage tank, the opening and closing state of the pipeline between the primary side water outlet of the heat exchanger and the second water inlet of the high-temperature heat storage tank is controlled by the valve T1, the secondary side water outlet of the heat exchanger is connected with the cold water supply pipeline loop and the heat supply pipeline loop through the three-way valve T2, in the cold water supply pipeline loop, the secondary side water outlet of the heat exchanger is connected with the water inlet of the absorption chiller, and the secondary side backwater outlet of the heat exchanger is connected with the water outlet of the absorption chiller, in the heat supply pipeline loop, the secondary side water outlet of the heat exchanger is connected with the system heat water circulation water supply pipeline, and the secondary side backwater outlet of the heat exchanger is directly connected with the system heat water circulation backwater pipeline.

[0072] The absorption chiller is used to generate cold energy by consuming heat energy, and the connection pipeline between the absorption chiller and the cold water circuit is controlled by a valve T3. The water chiller is used to generate cold energy by consuming electric energy, and the connection pipeline between the water chiller and the cold water circuit is controlled by a valve T4. The absorption chiller and the water chiller jointly meet the cold load demand of the terminal. The electric boiler is used to generate heat energy by consuming electric energy, and the connection pipeline between the electric boiler and the hot water circuit is controlled by a valve T5. The electric boiler and the heat exchange pipeline jointly meet the heat load demand of the terminal. The water circulation pipeline circuit takes water as an energy medium carrier to transmit the cold / heat energy generated by the energy system to the terminal, and the key pipeline nodes of the system cold water circulation circuit and the hot water circulation circuit are located at the connection between each energy supply device and the pipeline, the confluence of each branch pipeline, and the energy exchange position of the terminal load.

[0073] The multi-energy coupling Carnot cell water circulation energy system provided by the application organically combines renewable energy generation, Carnot cell, absorption refrigeration, electric heating, electric refrigeration and other devices, and optimizes the temperature, flow and other operating state information of each device and the water circulation circuit through a processing module, thereby effectively solving the multi-energy coupling problem of the system.

[0074] Embodiment 1

[0075] Please refer to Figure 2 , the flowchart of the multi-energy coupling Carnot cell water circulation energy system operation optimization method provided by the preferred embodiment of the application, and the following will be described in detail. Figure 2 The specific flowchart shown in the figure.

[0076] A multi-energy coupling Carnot cell water circulation energy system operation optimization method comprises the following steps: S1, collecting demand load samples, wherein the demand load samples comprise user electric demand, cold demand, heat demand and domestic hot water demand of each period;

[0077] S2, optimizing the operation of the multi-energy coupling Carnot cell water circulation energy system according to the user demand data collected in S1, to obtain an optimal operation strategy set of the multi-energy coupling Carnot cell water circulation energy system, and the operation comprises the following steps:

[0078] S2.1, constructing a mathematical model of the multi-energy coupling Carnot cell water circulation energy system, wherein the mathematical model comprises an objective function and a constraint condition, and the objective function minimizes the system operation cost; and the objective function is expressed as:

[0079]

[0080] In the formula, J is the objective function, S is the total number of scenarios, subscript s is the s-th scenario, and π sProbability of the s-th scenario; k0is the starting time of the rolling optimization scheduling stage, N K is the scheduling period, subscript k is the k-th time period; is the electricity purchase amount of the k-th time period under the s-th scenario, is the electricity sale amount of the k-th time period under the s-th scenario, is the electricity purchase price of the k-th time period, is the electricity sale price of the k-th time period, the price unit is RMB / kWh; τ is the time interval of the rolling optimization scheduling stage.

[0081] The related constraint conditions of the mathematical model of the multi-energy coupling Carnot battery water cycle energy system are as follows:

[0082] 1. Operation constraint of the water cycle sub-circuit of the chiller:

[0083]

[0084] wherein is the chiller operation power of the k-th time period under the s-th scenario; is the chiller refrigeration efficiency of the k-th time period under the s-th scenario; c W is the specific heat capacity of water, is the chiller water cycle pipeline switch state of the k-th time period under the s-th scenario, m EC is the flow of the chiller water cycle pipeline, is the chiller return water temperature of the k-th time period under the s-th scenario, is the chiller outlet water temperature of the k-th time period under the s-th scenario. The constraint accurately describes the inlet and outlet water temperatures and the flow of the chiller water cycle pipeline, and through the decision variable reflects the on-off state of the pipeline valve, which is conducive to the direct control of the system on the chiller water cycle pipeline.

[0085] 2. Operation constraint of the water cycle sub-circuit of the electric boiler:

[0086]

[0087] wherein is the electric boiler operation power of the k-th time period under the s-th scenario, η EB is the heating efficiency of the electric boiler; is the electric boiler water cycle pipeline switch state of the k-th time period under the s-th scenario, m EB is the flow of the electric boiler water cycle pipeline, is the electric boiler outlet water temperature of the k-th time period under the s-th scenario, Tsbkis the return water temperature of the electric boiler in the kth time period of the st scenario. This constraint accurately characterizes the inlet and outlet water temperature and flow rate of the electric boiler water circulation pipeline, while the decision variable reflects the on-off state of the pipeline valve, which is conducive to the direct control of the system for the electric boiler water circulation pipeline.

[0088] 3. Operation constraints of the Carnot cell:

[0089] a) Heat pump operation constraints

[0090]

[0091] wherein Pcbkis the charging power of the Carnot cell in the kth time period of the st scenario, η HP is the heating efficiency of the heat pump; Tsbkis the state of the hot water tank water circulation pipeline in the kth time period of the st scenario, indicates that the hot water tank water circulation pipeline is in the charging state in the kth time period of the st scenario, and vice versa; m LT,HT is the water flow rate from the low-temperature thermal storage tank to the high-temperature thermal storage tank, Tpbkis the outlet water temperature of the heat pump in the kth time period of the st scenario, Tsbkis the storage water temperature of the low-temperature thermal storage tank in the kth time period of the st scenario. This constraint accurately characterizes the inlet and outlet water temperature and flow rate of the heat pump water circulation pipeline, while the decision variable reflects the on-off state of the Carnot cell charging pipeline, which is conducive to the direct control of the system for the heat pump water circulation pipeline.

[0092] b) High-temperature thermal storage tank operation constraints

[0093]

[0094]

[0095]

[0096] wherein, indicates that the hot water tank water circulation pipeline is in the discharging state in the kth time period of the st scenario, and vice versa; Tsbk+1is the storage water volume of the high-temperature thermal storage tank in the k+1th time period of the st scenario, Tsbkis the storage water volume of the high-temperature thermal storage tank in the kth time period of the st scenario, m HT,LT is the water flow rate from the high-temperature thermal storage tank to the low-temperature thermal storage tank; Tsbkis the storage water temperature of the high-temperature thermal storage tank in the kth time period of the st scenario; and Qs,k+1is the heat transferred from the high-temperature thermal storage tank to the cold water circulation loop and the hot water circulation loop of the heat exchanger, respectively, U HT is the heat loss coefficient per unit area of the high-temperature thermal storage tank, A HT is the surface area of the high-temperature thermal storage tank, T ENV is the ambient temperature. This constraint accurately represents the thermal dynamic process, heat loss process, inlet and outlet water temperature, and flow rate of the water circulation pipeline of the high-temperature thermal storage tank, describes the operation mechanism of the high-temperature thermal storage tank, and accurately depicts the multi-energy coupling characteristics of the Carnot cell water circulation system.

[0097] c) Low-temperature thermal storage tank operation constraint

[0098]

[0099]

[0100] wherein, is the water storage amount of the low-temperature thermal storage tank in the k+1th period under the s th scenario, is the water storage amount of the low-temperature thermal storage tank in the kth period under the s th scenario, U LT is the heat loss coefficient per unit area of the low-temperature thermal storage tank, A LT is the surface area of the low-temperature thermal storage tank. This constraint accurately represents the thermal dynamic process, heat loss process, inlet and outlet water temperature, and flow rate of the water circulation pipeline of the low-temperature thermal storage tank, describes the operation mechanism of the low-temperature thermal storage tank, and accurately depicts the multi-energy coupling characteristics of the Carnot cell water circulation system.

[0101] d) Heat and power unit operation constraint

[0102]

[0103] wherein is the Carnot cell discharging power in the kth period under the s th scenario, η HE is the power generation efficiency of the heat and power unit. This constraint accurately depicts the inlet and outlet water temperature and flow rate of the water circulation pipeline of the heat and power unit, and reflects the on-off state of the Carnot cell energy release pipeline through the decision variable , which is conducive to the direct control of the system on the water circulation pipeline of the heat and power unit.

[0104] 4. Operation constraint of the absorption chiller water circulation sub-loop:

[0105]

[0106] wherein, η EX is the working efficiency of the heat exchanger, η AC is the refrigeration efficiency of the absorption chiller; is the on-off state of the absorption chiller water circulation pipeline in the kth period of the st scenario, m AC is the flow rate of the absorption chiller water circulation pipeline, is the outlet water temperature of the absorption chiller in the kth period of the st scenario. This constraint accurately describes the inlet and outlet water temperatures and the flow rate of the absorption chiller water circulation pipeline, and through the decision variable reflects the on-off state of the pipeline valve, which is conducive to direct control of the absorption chiller water circulation pipeline by the system.

[0107] 5. System operation constraints:

[0108]

[0109]

[0110]

[0111]

[0112] wherein, represents that the power grid is in the state of buying electricity in the kth period of the st scenario, and 0 otherwise; represents that the power grid is in the state of selling electricity in the kth period of the st scenario, and 0 otherwise.d k,s is the terminal electrical load in the kth period of the st scenario, q k,s is the terminal cooling load in the kth period of the st scenario, g k,s is the terminal heating load in the kth period of the st scenario. This constraint accurately describes the inlet and outlet water temperatures and the flow rate of the total cooling and heating water circulation pipeline, reflects the operation mechanism characteristics of the system energy supply, and is conducive to direct control of the total cooling and heating water circulation pipeline by the system.

[0113] S2.2, a sample parameter set is constructed, which includes a device parameter sample and a system environment parameter sample; the device parameter sample includes the initial state, rated capacity, rated power and energy efficiency ratio of the water chiller, electric boiler, Carnot cell and absorption chiller in the multi-energy coupled Carnot cell water circulation energy system; the system environment parameter sample includes the buying and selling electricity price, rolling optimization scheduling initial time and rolling optimization scheduling time interval.

[0114] S2.3, according to the collected demand load sample, a plurality of scenario trees of uncertain load are generated, scene reduction is performed, and a final scenario tree is obtained, the steps being as follows:

[0115] S2.3.1, according to the collected user electricity demand, cold demand, heat demand and hot water demand data, S scenarios are generated according to the given standard deviation X, and the random variable degree of freedom of each scenario is 3; the user electricity demand, cold demand, heat demand and hot water demand data all follow normal distribution, the mean of each normal distribution is the corresponding demand data value collected, and the standard deviation X is 3%-20% of the mean;

[0116] S2.3.2, the Euclidean distance of random variables between all scenarios is calculated;

[0117] S2.3.3, delete any one of the pair of scenarios with the minimum Euclidean distance, and add the probability of the deleted scenario to the scenario with the minimum Euclidean distance, and change the probability of the deleted scenario to zero;

[0118] S2.3.4, repeat the above steps Y times, wherein Y=(0.8-0.99)*S, and finally obtain a final scenario tree containing S-Y scenarios.

[0119] S2.4, based on the sample parameter set constructed in S2.2 and the final scenario tree obtained in S2.3, the optimal operation strategy set in the system scheduling period is obtained by solving the mathematical model constructed in S201 using a rolling optimization method, the optimal operation strategy set includes system buying and selling electricity quantity and operation cost, operation power and outlet water temperature of each device, temperature and flow of key nodes such as connection between each energy supply device and pipeline, connection between energy storage device charging and discharging pipeline, convergence of each branch pipeline and energy exchange at the end of load. The steps of solving the mathematical model by rolling optimization method are as follows:

[0120] S2.4.1, in each scenario, the scheduling period time domain is shortened from [1, K] to [k, k+τ), wherein the value of τ is 6, and the initial objective function J0 of the system is calculated according to the obtained device parameter sample and system environment parameter sample;

[0121] S2.4.2, in each scenario, the mathematical model established in S2.1 is solved in the time domain [k, k+τ), and the optimal operation strategy set of the time domain [k, k+τ) is obtained, the optimal operation strategy set of the time domain [k, k+τ) includes the optimal operation strategy of k period, k+1 period, k+2 period …… k+τ period, and only the optimal operation strategy set of k period is taken as the system control setting value of k period;

[0122] S2.4.3, in each scenario, the system objective function J1 and the optimal operation strategy set of the system in the time domain [k+1, k+1+τ) are calculated, and only the optimal operation strategy set of k+1 period is taken as the system control setting value of k+1 period;

[0123] S2.4.4, repeat S2.4.3, the entire optimization interval rolls forward with time until the optimal operation strategy set of the time domain [K-τ, K] is calculated, and the optimal operation strategy set of the entire scheduling period [1, K] is obtained.

[0124] S3, the optimal operation strategy set obtained according to S2 is used to control the multi-energy coupled Carnot battery water cycle energy system in real time.

[0125] Embodiment 2

[0126] Please refer to Figure 3 The function module schematic diagram of the multi-energy coupled Carnot battery water cycle energy system optimization device provided by the preferred embodiment of the application, characterized by comprising a perception analysis module 110, an optimization decision module 120 and a control scheduling module 130; the perception analysis module 110 is used to collect the electricity, cold, heat and domestic hot water demand data of users, and transmit the data to the optimization decision module 120; the optimization decision module 120 generates a scenario tree of uncertain load according to the obtained demand data, and solves the model to obtain the optimal operation strategy set of the multi-energy coupled Carnot battery water cycle energy system, and transmits the optimal operation strategy set to the control scheduling module 130; the control scheduling module 130 is connected with the key nodes such as the connection places of each energy supply device and pipeline, the connection places of energy storage device charging and discharging pipeline, the confluence places of each branch pipeline, and the energy exchange places of terminal load through data lines, and controls according to the corresponding optimization decision quantity.

[0127] The perception analysis module 110 comprises a temperature sensor, a flow sensor, a water level sensor and a data processing and transmission device, the temperature sensor is used to collect the real-time data of supply and return water temperature of the key nodes of each device sub-cycle loop and water cycle pipeline loop of the multi-energy coupled Carnot battery water cycle energy system; the flow sensor is used to collect the supply and return water flow of the key nodes of each device sub-cycle loop and water cycle pipeline loop of the multi-energy coupled Carnot battery water cycle energy system; the water level sensor is used to collect the water storage amount of the high-temperature heat storage tank and the low-temperature heat storage tank; the data processing and transmission device is used for data preprocessing and cold and heat load data calculation, and is also used for transmission communication with the optimization decision module 120 and the outside world.

[0128] The optimization decision module 120 comprises an initialization module, a sample construction module and a solving module. The initialization module is used for initializing the optimization decision module 120 and determining relevant constraint conditions and objective functions, and constructing a mathematical model of the multi-energy coupled Carnot battery water cycle energy system; the sample construction module is used for constructing a sample parameter set, which comprises a device parameter sample and a system environment parameter sample, wherein the device parameter sample comprises initial states, rated capacities, rated powers and energy efficiency ratios of a water chiller, an electric boiler, a Carnot battery unit and an absorption chiller in the multi-energy coupled Carnot battery water cycle energy system; and the system environment parameter sample comprises a buying and selling electricity price, a rolling optimization scheduling initial time and a rolling optimization scheduling time interval; and the solving module is used for solving the mathematical model by using a rolling optimization method on the constructed sample parameter set, so as to obtain an optimal operation strategy set in a system scheduling period.

[0129] The control scheduling module 130 comprises a communication connection data line, temperature and flow control devices of key nodes such as connection places of each energy supply device and a pipeline, connection places of energy storage devices and a charging and discharging pipeline, convergence places of each branch pipeline and an end load energy exchange place. The communication connection data line is used for information interaction between each device; and the temperature and flow control devices of the key nodes are used for controlling water supply and return temperatures and flow sizes of the key nodes.

[0130] Embodiment 3

[0131] The preferred embodiment of the present application provides a multi-energy coupled Carnot battery water cycle energy system operation optimization device, which is used for executing the operation optimization method of the multi-energy coupled Carnot battery water cycle energy system. The function modules of the optimization decision module 120 can be divided according to the method examples. For example, each function module can be divided according to each function, or two functions can be integrated in one processing module. The integrated module can be realized in the form of hardware or in the form of a software function module. It should be noted that the division of the modules in the embodiments of the present application is illustrative, and is only a logical function division. When actually implemented, another division mode can be used.

[0132] Embodiment 4

[0133] Please refer to Figure 4 In the case of dividing each function module according to each function, Figure 4A first possible structure of the optimization decision module in the preferred embodiment is shown, including: an initialization module 121, a sample construction module 122, and an optimization module 123. The initialization module 121 is configured to support the multi-energy coupled Carnot battery water cycle energy system operation optimization device to perform S201; the sample construction module 122 is configured to support the multi-energy coupled Carnot battery water cycle energy system operation optimization device to perform S202; the optimization module 123 is configured to support the multi-energy coupled Carnot battery water cycle energy system operation optimization device to perform S203 and S204; wherein all the related content of each step involved in the above method embodiment can be cited to the function description of the corresponding function module, and will not be repeated here.

[0134] Embodiment 5

[0135] Please refer to Figure 5 In the case of using an integrated unit, Figure 5 A second possible structure of the optimization decision module in the preferred embodiment is shown, including: a data processing unit 124, a data storage unit 125, and a data output unit 126. The data processing unit 124 is configured to control and manage the actions of the multi-energy coupled Carnot battery water cycle energy system operation optimization device, for example, the data processing unit 124 is configured to support the multi-energy coupled Carnot battery water cycle energy system operation optimization device to perform S201, S202, S203 and S204 in the above method; the data storage unit 125 is configured to store the program code and related data of the multi-energy coupled Carnot battery water cycle energy system operation optimization device; the data transmission unit 126 is configured to support the input and output data operation of the user.

[0136] The data processing unit 124 can be, but is not limited to, a processor or a controller, for example, a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logical blocks, modules and circuits described in combination with the disclosure. The data processing unit 124 can also be a combination of computing functions, such as one or more microprocessor combinations, combinations of DSP and microprocessor, etc.

[0137] The data transmission unit 126 can be, but is not limited to, a mouse and a keyboard, etc.

[0138] When the data processing unit 124 is a processor and the data storage unit 125 is a memory, the multi-energy coupled Carnot cell water cycle energy system operation optimization device involved in the best embodiment of the present application can be a multi-energy coupled Carnot cell water cycle energy system operation optimization device as follows.

[0139] Embodiment 6

[0140] Please refer to Figure 6 For the possible structure of the optimization decision module in another best embodiment of the present application, it includes a processor 127, a memory 128 and a bus 129; the memory 128 is used to store computer execution instructions; the processor 127 and the memory 128 are connected through the bus 129; when the multi-energy coupled Carnot cell water cycle energy system operation optimization device is running, the processor 127 executes the computer execution instructions stored in the memory 128 to execute S201, S202, S203 and S204 of the multi-energy coupled Carnot cell water cycle energy system operation optimization method as described above. The bus 129 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc.; the bus 129 can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 6 In the figure, only one thick line is used to represent, but it does not mean that there is only one bus or one type of bus.

[0141] The data storage unit 125 and the memory 128 can be, but are not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable read-only memory (Erasable Programmable Read-Only Memory, EPROM), electrically erasable read-only memory (Electric Erasable Programmable Read-Only Memory, EEPROM), etc.

[0142] Since the multi-energy coupled Carnot cell water cycle energy system operation optimization device provided by the best embodiment of the present application can be used to execute the multi-energy coupled Carnot cell water cycle energy system operation optimization method described above, the technical effects it can obtain can refer to the method embodiment described above, and the present embodiment will not be repeated here.

[0143] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that can be accessed by a computer or include one or more data storage devices such as servers, data centers, etc. integrated with the medium. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)), etc.

[0144] Although the present application has been described in connection with specific features thereof and the embodiments thereof, it will be evident that various modifications and combinations can be made thereto without departing from the spirit and scope of the application. Accordingly, the description and drawings are to be regarded as illustrative in nature and are not to be regarded as limiting the scope of the application as defined in the appended claims. Obviously, various modifications and changes can be made to the present application by those skilled in the art without departing from the spirit and scope of the present application. Thus, it is intended that the present application encompass all such modifications and changes and, accordingly, the above description is to be construed as illustrative only and is for the purpose of teaching the general scope of the present application. The embodiments disclosed in the specification and the drawings are to be considered as merely illustrative and not restrictive in nature. Obviously, various modifications and changes can be made to the present application by those skilled in the art without departing from the spirit and scope of the present application. Thus, if these modifications and changes belong to the scope of the claims of the present application and equivalent technology thereof, the present application is intended to include these modifications and changes.

[0145] From the technical common sense, the present application can be realized by other embodiments without departing from the spirit or essential characteristics thereof. Therefore, the above disclosed embodiments are merely illustrative in all aspects, and are not the only ones. All changes within the scope of the present application or within the scope equivalent to the present application are included in the present application.

Claims

1. A method for optimizing the operation of a multi-energy coupled Carnot battery water cycle energy system, characterized in that, Includes the following steps: S1. Collect demand load samples, which include users' electricity demand, cooling demand, heating demand and domestic hot water demand for each time period; S2. Based on the user demand data collected in S1, optimize the operation of the Carnot battery water cycle energy system, which couples multiple energy sources such as electricity, cooling, heating, and domestic hot water, to obtain the optimal operating strategy set for the multi-energy coupled Carnot battery water cycle energy system. This specifically includes the following steps: S2.1 Construct a mathematical model of a multi-energy coupled Carnot battery water cycle energy system. The mathematical model includes an objective function and constraints. The objective function minimizes the system operating cost. S2.2 Construct a sample parameter set, which includes a device parameter sample and a system environment parameter sample; S2.

3. Based on the demand load sample, generate multiple scenario trees for uncertain loads, perform scenario reduction, and obtain the final scenario tree; S2.

4. Based on the sample parameter set constructed in S2.2 and the final scenario tree obtained in S2.3, solve the mathematical model constructed in S201 to obtain the optimal operating strategy set within the system scheduling cycle; S3. Perform real-time control of the multi-energy coupled Carnot battery water cycle energy system based on the optimal operating strategy set obtained in S2. In S2.1, the constraints include: Operating constraints of the water circulation sub-loop of the chiller unit: in For the first s In the scenario of the first k The operating power of the chiller unit during each time period; For the s-th scenario, the first... k The cooling efficiency of the chiller unit during a specific time period; The specific heat capacity of water, For the s-th scenario, the first... k The on / off status of the chiller unit's water circulation pipeline during a specific time period. This refers to the flow rate of the water circulation pipes in the chiller unit. For the s-th scenario, the first... k The return water temperature of the chiller unit during a certain period. For the s-th scenario, the first... k The outlet water temperature of the chiller unit during each time period; Operating constraints of the water circulation sub-loop of the electric boiler: in For the first s In the scenario of the first k The operating power of the electric boiler during each time period The heating efficiency of the electric boiler; For the s-th scenario, the first... k The on / off status of the electric boiler water circulation pipes during a specific time period. The flow rate of the water circulation pipe in the electric boiler. For the s-th scenario, the first... k The outlet water temperature of the electric boiler at different time periods, For the s-th scenario, the first... k The return water temperature of the electric boiler during each time period; The operational constraints of the Carnot battery cell include heat pump operational constraints, high-temperature thermal storage tank operational constraints, low-temperature thermal storage tank operational constraints, and thermal power unit operational constraints. Operating constraints of the water circulation sub-loop in an absorption chiller: in, For the working efficiency of the heat exchanger, The refrigeration efficiency of an absorption chiller; For the s-th scenario, the first... k The on / off status of the absorption chiller water circulation pipeline during each time period. This refers to the flow rate of the water circulation pipe in the absorption chiller. For the s-th scenario, the first... k The outlet water temperature of the absorption chiller during each time period; System operational constraints; in, In the s-th scenario, the first... k The power grid is in a state of purchasing electricity during a certain period, and 0 otherwise; In the s-th scenario, the first... k The power grid is in a selling state during a certain period, and 0 otherwise; For the s-th scenario, the first... k The end electrical load of each time period For the s-th scenario, the first... k The end-of-period cooling load, For the s-th scenario, the first... k The end heat load of each time period; The operating constraints of the heat pump are: , in For the first s In the scenario of the first k The charging power of the Cano battery during each time period, The heating efficiency of the heat pump; For the s-th scenario, the first... k Status of the hot water tank's water circulation pipes at different times. In the s-th scenario, the first... k The hot water tank's water circulation pipe is in a charged state during certain time periods, and 0 otherwise; This refers to the water flow rate from the low-temperature thermal storage tank to the high-temperature thermal storage tank. For the s-th scenario, the first... k The heat pump outlet water temperature at different times For the s-th scenario, the first... k The water temperature in the low-temperature thermal storage tank during each time period; The operating constraints of the high-temperature thermal storage tank are: ， in, In the s-th scenario, the first... k During a certain period, the hot water tank's water circulation pipe is in a state of releasing energy, and vice versa; For the first s In the scenario of the first k+1 The water storage capacity of the high-temperature thermal storage tank during each time period. For the first s In the scenario of the first k The water storage capacity of the high-temperature thermal storage tank during each time period. The water flow rate from the high-temperature thermal storage tank to the low-temperature thermal storage tank; For the s-th scenario, the first... k The water temperature in the high-temperature thermal storage tank during each time period; and These represent the heat transferred from the high-temperature heat storage tank to the cold water circulation loop and the hot water circulation loop of the heat exchanger, respectively. This is the heat loss coefficient per unit area of ​​the high-temperature thermal storage tank. The surface area of ​​the high-temperature thermal storage tank. Ambient temperature; The operating constraints of the cryogenic thermal storage tank are: ， in, For the first s In the scenario of the first k+1 The water storage capacity of the low-temperature thermal storage tank during each time period. For the first s In the scenario of the first k The water storage capacity of the low-temperature thermal storage tank during each time period. This is the heat loss coefficient per unit area of ​​the cryogenic thermal storage tank. The surface area of ​​the cryogenic thermal storage tank; The operating constraints of the thermal power unit are: , in For the first s In the scenario of the first k The discharge power of the Carnot battery during each time period, This refers to the power generation efficiency of the thermal power unit.

2. The operation optimization method for a multi-energy coupled Carnot battery water cycle energy system according to claim 1, characterized in that, S2.3 includes the following steps: S2.3.1 Based on the collected user electricity demand, cooling demand, heating demand, and domestic hot water demand data, respectively, according to the given standard deviation... X generate S A scenario; S2.3.2 Calculate the Euclidean distance between each pair of random variables in all scenarios; S2.3.3 Delete any one of the two scenarios with the smallest Euclidean distance, add the probability of the deleted scenario to the scenario with the smallest Euclidean distance, and set the probability of the deleted scenario to zero. S2.3.4 Repeat the above steps Y-1 times, where Y = (0.8~0.99)×S, to finally obtain the final scenario tree containing SY scenarios.

3. The operation optimization method for a multi-energy coupled Carnot battery water cycle energy system according to claim 1, characterized in that, In S2.4, the optimal set of operating strategies within the system scheduling cycle is obtained by solving the mathematical model constructed in S201 using the rolling optimization method.

4. The method for optimizing the operation of a multi-energy coupled Carnot battery water cycle energy system according to claim 1 or 3, characterized in that, S2.4 includes the following steps: S2.4.1 In each scenario, the scheduling cycle time domain is shortened from [1,K] to [ k , Based on the obtained equipment parameter samples and system environment parameter samples, calculate the initial objective function of the system. J 0; S2.4.2, In each scenario, in the time domain [ k , Solving the mathematical model established in S2.1 within the time domain yields the optimal operating strategy set. k , The optimal set of operating strategies includes Time period k, time period k+1, time period k+2... The optimal operating strategy for a given time period is to select only... k The optimal set of operating strategies for a given time period is used as k Time period system control settings; S2.4.3, In each scenario, calculate in the time domain [ , Internal system objective function J 1. The optimal operating strategy set of the system is selected, and only the optimal operating strategy set of time period k+1 is taken as the system control set value for time period k+1. S2.4.4, Repeat S2.4.3, the entire optimization interval rolls forward with time until the time domain is calculated. , The optimal set of operating strategies for the entire scheduling cycle [1,K] is obtained by finding the optimal set of operating strategies for the entire scheduling cycle [1,K].

5. A multi-energy coupled Carnot battery water cycle energy system optimization device, used to implement the method of claim 1, characterized in that, It includes a perception and analysis module, an optimization decision-making module, and a control and scheduling module. The perception and analysis module is used to collect users' electricity, cooling, heating, and domestic hot water demand data and transmit the data to the optimization decision-making module. The optimization decision-making module generates a final scenario tree of uncertain loads based on the obtained demand data, solves the model to obtain the optimal operating strategy set of the multi-energy coupled Carnot battery water cycle energy system, and transmits the optimal operating strategy set to the control and scheduling module. The control and scheduling module is used to control key nodes such as the connection points between each energy supply device and pipeline, the connection points between the charging and discharging pipelines of the energy storage device, the confluence points of each branch pipeline, and the energy exchange points of the end load, according to the operation strategy set.

6. The multi-energy coupled Carnot battery water cycle energy system optimization device according to claim 5, characterized in that, The optimization decision-making module includes an initialization module, a sample construction module, and a solution module; The initialization module is used to initialize the optimization decision module and determine the constraints and objective function of the multi-energy coupled Carnot battery water cycle energy system, and to construct the mathematical model of the multi-energy coupled Carnot battery water cycle energy system. The sample construction module is used to construct a sample parameter set, which includes a device parameter sample and a system environment parameter sample. The solution module is used to solve the constructed mathematical model and sample parameter set using a rolling optimization method to obtain the optimal operating strategy set within the system scheduling cycle.

7. An optimization device for a multi-energy coupled Carnot battery water cycle energy system, characterized in that, The optimization decision-making module includes a data processing unit, a data storage unit, and a data transmission unit; The data processing unit is used to support the multi-energy coupled Carnot battery water cycle energy system optimization device in executing the optimization method according to any one of claims 1-4; The storage unit is used to store the program code and data of the multi-energy coupled Carnot battery water cycle energy system optimization device; the data transmission unit realizes information interaction with the outside world.

8. A device for optimizing a multi-energy coupled Carnot battery water cycle energy system, characterized in that, The optimization decision module includes a processor, a bus, and a memory; the processor is connected to the memory via the bus and is used to call the computer program and data in the memory in real time via the bus to execute the optimization method according to any one of claims 1-4; The memory is used to store the computer program and data of the multi-energy water circulation system constant temperature water supply optimization device.

Images