Multi-heat source cooperative heat supply energy cascade utilization optimization method

Abstract

The application provides a multi-heat-source cooperative heat supply energy gradient utilization optimization method. By orderly combining four energy supply forms of a heat supply secondary network, a ground source, a water source and an air source, a multi-heat-source energy gradient control method based on a heat load demand gap is established, a multi-energy heat supply control system based on an autonomous controllable hardware architecture is established, multi-stage optimized utilization of heat supply energy is realized, the dependence on a single heat source is reduced to the maximum extent, the diversification of heat supply carriers is significantly improved, and a new clean energy heat supply mode is realized.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of multi-energy complementary comprehensive energy application, and particularly relates to a multi-heat-source coordinated heat supply energy cascade utilization optimization method. BACKGROUND

[0002] Multi-energy complementary comprehensive energy system optimization control technology is a key technology for breaking the existing mode of separate planning, separate design and independent operation of each energy supply and use system, realizing multi-energy complementary and stable operation of the comprehensive energy system, and achieving the purpose of efficient energy utilization and renewable energy consumption.

[0003] At present, multi-type energy cannot form efficient energy utilization due to its inherent characteristics, and the energy in the system also lacks comprehensive optimization thinking of cascade utilization, so it is difficult to implement the development vision of clean, efficient and low-carbon.

[0004] In summary, in order to realize flexible consumption of multi-type energy and advocate clean and efficient energy utilization, it is necessary to carry out more in-depth technical integration research on multi-energy coupling control system. SUMMARY

[0005] The application aims to solve the problems in the prior art and provides a multi-heat-source coordinated heat supply energy cascade utilization optimization method.

[0006] The application is implemented through the following technical scheme, and the application provides a multi-heat-source coordinated heat supply energy cascade utilization optimization method, which comprises the following steps:

[0007] Step 1: controller self-checking and resetting all devices, that is, each subsystem pump and electric actuator is adjusted to the closed state;

[0008] Step 2: all devices meet the starting permission state, and the secondary network system auxiliary equipment, return water electric actuator, water inlet electric actuator and secondary network circulating pump are started in turn in priority;

[0009] Step 3: all secondary network devices run or start signal feedback are accurate, and the ground source system auxiliary equipment, return water electric actuator, water inlet electric actuator and ground source side circulating pump are started in turn in priority;

[0010] Step 4: all ground source devices run or start signal feedback are accurate, and the water source system auxiliary equipment, return water electric actuator, water inlet electric actuator and water source circulating pump are started in turn in priority;

[0011] Step 5: All water source equipment operation or start signal feedback is accurate, priority to start air source system ancillary equipment, return water electric actuator, water inlet electric actuator, air source side circulating pump in turn;

[0012] Step 6: All air source equipment operation or start signal feedback is accurate, the controller at this moment according to the heat load demand optimization;

[0013] Step 7: Start step sequence is completed, the power distribution of multi-energy heat supply control system after starting is optimized and adjusted by load optimization scheduling distribution method;

[0014] Step 8: Multi-energy heat supply control system automatic stop sequence, in turn according to the order of air source, water source, ground source unit stop running, first close the unit return water electric actuator, then close the water inlet electric actuator, finally stop the unit, if the above-mentioned unit is not started, then skip the part of stopping the unit.

[0015] Further, in step 2, the default of secondary network circulating pump control instruction output is 25Hz.

[0016] Further, in step 3, the default of ground source side circulating pump control instruction output is 0Hz.

[0017] Further, in step 4, the default of water source circulating pump control instruction output is 0Hz.

[0018] Further, in step 5, the default of air source side circulating pump control instruction output is 0Hz.

[0019] Further, the load optimization scheduling distribution method is specifically:

[0020] Step 1: Collecting heat supply secondary network water supply, secondary network return water and outdoor environment temperature at regular intervals, the sampling time interval is 5s;

[0021] Step 2: Periodically calculating the heat supply capacity of heat supply secondary network, ground source, water source and air source, the cycle time is 5s, defining t instantaneous moment, the heat supply capacity of each subsystem is calculated by the following formula, 0 t时刻瞬时供热 =(T 当前系统供水温度上限 -T 当前系统回水温度 )×Q 时刻时流量 When the instantaneous flow at T moment is 0, the heat supply capacity at T moment is 0, and the heat supply capacity will not appear negative value, that is, the heat supply system will not absorb heat from the heat network;

[0022] Step 3: On the premise that heat supply secondary network, ground source, water source and air source four sets of heat supply subsystems are not fault, the energy supply mode is selected to run in heat supply secondary network mode by default, marked as label X1, and the other modes are ground source label X2, water source label X3 and air source label X4 in turn; Define energy consumption penalty factor Z, the greater the value of Z represents the higher the energy consumption index, let Z二次网 = 0, Z 水源 = 0.54, Z 地源 = 0.23, Z 空气源 = 0.78;

[0023] Step four: define the heat user demand as a fixed value, the indoor environment temperature changes, and the heat user load demand is determined by the following formula

[0024] Step five: according to the target constraint condition of the minimum energy consumption of the multi-energy heat supply control system, the load power distribution target optimization is carried out, and the instantaneous control instruction outputs of the subsystems are P X1 , P X2 , P X3 , P X4 When the optimization result is P Xi is 0, it means that the above-mentioned subsystem does not need to be started, and the digital output DO of the corresponding control instruction is 0; when the optimization result is P Xi is greater than 0, it means that the output should reach 100*P Xi % of the rated power.

[0025] Further, the target constraint condition is specifically:

[0026]

[0027] Further, the load optimization scheduling distribution method completes semantic logic conversion through the ladder diagram language of the self-controllable programmable logic controller (PLC), and realizes process control on the process through the analog output (AO) and digital output (DO) channels of the controller.

[0028] The present application provides an electronic device, comprising a memory and a processor, the memory stores a computer program, and the processor implements the steps of the multi-heat source collaborative heat supply energy cascade utilization optimization method when executing the computer program.

[0029] The present application provides a computer readable storage medium for storing computer instructions, which are executed by a processor to implement the steps of the multi-heat source collaborative heat supply energy cascade utilization optimization method.

[0030] Compared with the prior art, the present application has the following advantages:

[0031] The present application provides a multi-heat source collaborative heat supply energy cascade utilization optimization method. The method is a heat supply energy cascade utilization optimization method realized by a multi-energy heat supply control system based on a self-controllable hardware architecture, which maximizes the degree of dependence on a single heat source, significantly improves the diversification of heat supply carriers, and realizes a new mode of clean energy heat supply. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings described in the following are only a part of the embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor based on the provided drawings.

[0033] Figure 1 The flow chart of the method for optimizing the energy cascade utilization of the multi-heat-source cooperative heat supply. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present application will be clearly and completely described in combination with 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. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.

[0035] In combination with Figure 1 The present application provides a method for optimizing the energy cascade utilization of multi-heat-source cooperative heat supply, which comprises the following steps:

[0036] Step 1: The controller self-checks and resets all devices, i.e. each subsystem pump and electric actuator is adjusted to the closed state.

[0037] Step 2: All devices meet the starting permission state, and the secondary network system auxiliary equipment, return water electric actuator, inlet water electric actuator and secondary network circulating pump are started in turn in priority; in step 2, the control instruction output of the secondary network circulating pump is defaulted as 25 Hz.

[0038] Step 3: All secondary network device running or starting signal feedbacks are accurate, and the ground source system auxiliary equipment, return water electric actuator, inlet water electric actuator and ground source side circulating pump are started in turn in priority; in step 3, the control instruction output of the ground source side circulating pump is defaulted as 0 Hz.

[0039] Step 4: All ground source device running or starting signal feedbacks are accurate, and the water source system auxiliary equipment, return water electric actuator, inlet water electric actuator and water source circulating pump are started in turn in priority; in step 4, the control instruction output of the water source circulating pump is defaulted as 0 Hz.

[0040] Step 5: All water source device running or starting signal feedbacks are accurate, and the air source system auxiliary equipment, return water electric actuator, inlet water electric actuator and air source side circulating pump are started in turn in priority; in step 5, the control instruction output of the air source side circulating pump is defaulted as 0 Hz.

[0041] Step 6: All air source equipment operation or start signal feedback is accurate, the controller at this moment according to the heat load demand optimization;

[0042] Step 7: start step sequence is completed, the power distribution of multi-energy heating control system after starting is optimized and adjusted by load optimization scheduling distribution method;

[0043] Step 8: multi-energy heating control system automatic stop sequence, in turn according to the sequence of air source, water source, ground source unit stop operation, first close the unit return water electric actuator, then close the water inlet electric actuator, finally stop the unit, if the above-mentioned unit is not started, then skip the part of stopping the unit.

[0044] The load optimization scheduling distribution method is specifically:

[0045] Step 1: collect the heating secondary network water supply, secondary network return water and outdoor environment temperature at regular intervals, the sampling time interval is 5s;

[0046] Step 2: periodically calculate the heating capacity of heating secondary network, ground source, water source and air source, the cycle time is 5s, define t instantaneous moment, the heating capacity of each subsystem is calculated by the following formula, θ 时刻瞬时供热 =(T 当前系统供水温度上限 -T 当前系统回水温度 )×Q t时刻瞬时流量 , when the instantaneous flow at T time is 0, the heating capacity at T time is 0, and the heating capacity will not appear negative value, that is, the heating system will not absorb heat from the heat network;

[0047] Step 3: under the premise that the heating secondary network, ground source, water source and air source four sets of heating subsystems are not fault, the energy supply mode is selected as the heating secondary network mode by default, which is marked as X1, and the other modes are ground source X2, water source X3 and air source X4 in turn; define energy consumption penalty factor Z, the larger the value of Z represents the higher the energy consumption index, let Z 二次网 =0, Z 水源 =0.54, Z 地源 =0.23, Z 空气源 =0.78;

[0048] Step 4: define the heat user demand as a fixed value, the indoor environment temperature changes, and the heat user load demand is determined by the following formula

[0049] Step 5: according to the target constraint condition of the lowest energy consumption of multi-energy heating control system, the load power distribution target optimization is carried out, and the instantaneous control instruction output of each subsystem is P X1 , P X2 , P X3 , P X4When the optimization result is P Xi 0, it means that the subsystem does not need to be started, and the digital output DO corresponding to the control instruction is output as 0; when the optimization result is P Xi greater than 0, it means that the output should reach 100*P Xi % of the rated power.

[0050] The target constraint condition is specifically:

[0051]

[0052] The load optimization scheduling distribution method completes semantic logic conversion through the ladder language of the autonomous controllable programmable logic controller (PLC), and realizes process control on the process through the analog output (AO) and digital output (DO) channels of the controller.

[0053] The application provides a multi-heat-source cooperative heat supply energy gradient utilization optimization method, which combines four energy supply forms of a heat supply secondary network, a ground source, a water source and an air source in an orderly manner, establishes a multi-heat-source energy gradient control method based on a heat load demand gap, and realizes multi-level optimization utilization of heat supply energy based on a multi-energy heat supply control system with an autonomous controllable hardware architecture, so that the dependence on a single heat source is reduced to the maximum extent, the diversification of heat supply carriers is significantly improved, and a new clean energy heat supply mode is realized.

[0054] The application provides an electronic device, which comprises a memory and a processor, the memory stores a computer program, and the processor realizes the steps of the multi-heat-source cooperative heat supply energy gradient utilization optimization method when executing the computer program.

[0055] The application provides a computer readable storage medium for storing computer instructions, and the computer instructions realize the steps of the multi-heat-source cooperative heat supply energy gradient utilization optimization method when executed by a processor.

[0056] The memory in the embodiments of the present application can be a volatile memory or a nonvolatile memory, or can include both volatile and nonvolatile memory. Among them, the nonvolatile memory can be a read only memory (ROM), a programmable ROM (PROM), an erasable programmable ROM (EPROM), an electrically EPROM (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM) used as an external cache. By way of example, and not limitation, many forms of RAM can be used, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous dynamic RAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DRRAM). It is noted that the memory of the methods described herein is intended to include, but not be limited to, these and any other suitable types of memory.

[0057] 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 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 transferred from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transferred 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 a data storage device such as a server, data center, etc. integrated with one or more available media. The available media can be magnetic media (such as floppy disk, hard disk, magnetic tape), optical media (such as high-density digital video disc (digital video disc, DVD)), or semiconductor media (such as solid state disc (solid state disc, SSD)) and the like.

[0058] In the implementation process, each step of the above method can be completed by integrated logic circuit of hardware in the processor or instruction in the form of software. The steps of the method disclosed in the embodiments of the present application can be directly embodied as hardware processor execution or combined execution by hardware and software modules in the processor. The software module can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, register and other mature storage media in the art. The storage medium is located in the memory, and the processor reads the information in the memory and combines the hardware to complete the steps of the above method. To avoid repetition, it will not be described in detail here.

[0059] It should be noted that the processor in the embodiments of the present application can be an integrated circuit chip with a signal processing capability. In the implementation process, each step of the method embodiments can be completed by the integrated logic circuit of hardware in the processor or the instructions in the form of software. The processor mentioned above can be a general processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The disclosed methods, steps and logic block diagrams in the embodiments of the present application can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as a hardware code processor for execution, or a combination of hardware and software modules in the code processor for execution. The software module can be located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register or other mature storage medium in the art. The storage medium is located in the memory, and the processor reads the information in the memory, and combines the hardware to complete the steps of the above method.

[0060] The above describes in detail the multi-heat source collaborative heat supply energy cascade utilization optimization method proposed in the present application. The principles and implementation manners of the present application are described by using specific examples. The above embodiment is only used to help understand the method of the present application and its core idea; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation manner and application range will be changed, and the above description should not be understood as a limitation of the present application.

Claims

1. A multi-heat source coordinated heat supply energy cascade utilization optimization method, characterized in that, The method comprises the following steps: Step 1: controller self-checking and resetting all devices, i.e. each subsystem pump, electric actuator is adjusted to the closed state; Step 2: all devices meet the starting permission state, and the secondary network system accessory devices, return water electric actuators, water inlet electric actuators and secondary network circulating pumps are started in turn; Step 3: all secondary network devices run or the starting signal feedback is accurate, and the ground source system accessory devices, return water electric actuators, water inlet electric actuators and ground source side circulating pumps are started in turn; Step 4: all ground source devices run or the starting signal feedback is accurate, and the water source system accessory devices, return water electric actuators, water inlet electric actuators and water source circulating pumps are started in turn; Step 5: all water source devices run or the starting signal feedback is accurate, and the air source system accessory devices, return water electric actuators, water inlet electric actuators and air source side circulating pumps are started in turn; Step 6: all air source devices run or the starting signal feedback is accurate, and the controller optimizes according to the heat load demand at this moment; Step 7: the starting step sequence is completed, and the power distribution of the multi-energy heat supply control system after starting is optimized and adjusted by the load optimization scheduling distribution method; Step 8: the multi-energy heat supply control system automatically stops the step sequence, and is stopped in turn according to the order of air source, water source and ground source units, the return water electric actuators of the units are closed first, then the water inlet electric actuators are closed, and finally the units are stopped, if the above-mentioned units are not started, the part of stopping the units is skipped; The load optimization scheduling distribution method specifically comprises the following steps: Step one: the secondary network water supply, secondary network return water and outdoor environment temperature are collected at a time interval of 5s; Step two: the heat supply capacity of secondary network, ground source, water source and air source is calculated, the cycle time is 5s, the instantaneous time is defined as t, and the heat supply capacity of each subsystem is calculated by the following formula, When the instantaneous flow at T time is 0, the heat supply capacity at T time is 0, and the heat supply capacity will not appear negative value, that is, the heat supply system will not absorb heat from the heat network; Step three: under the premise that the four sets of heating subsystems of the heat supply secondary network, the ground source, the water source and the air source are all not faulty, the energy supply mode is defaulted to select the heat supply secondary network mode to run, which is marked as label X1, and the other modes are in turn the ground source label X2, the water source label X3 and the air source label X4; define the energy consumption penalty factor Z, the larger the value of Z represents the higher the energy consumption index, and let Z 二次网 =0, Z 水源 =0.54, Z 地源 =0.23, Z 空气源 =0.78; Step four: Define the thermal user demand as a fixed value, the indoor environment temperature changes, the thermal user load demand is determined by the following formula ; Step five: Optimize the load power distribution target according to the target constraint condition of the minimum energy consumption of the multi-energy heating control system, and the instantaneous control instruction output of each subsystem is P X1 , P X2 , P X3 , P X4 . When the optimization result is P Xi =0, it means that the above subsystem does not need to start, and the digital output DO of the corresponding control instruction is 0; when the optimization result is P Xi >0, it means that the output should reach 100*P Xi % of the rated power. The target constraint condition specifically comprises: 。 2. The method of claim 1, wherein, In step 2, the secondary network circulating pump control instruction output is 25Hz by default.

3. The method of claim 1, wherein, In step 3, the ground source side circulating pump control instruction output is 0Hz by default.

4. The method of claim 1, wherein, In step 4, the water source circulating pump control instruction output is 0Hz by default.

5. The method of claim 1, wherein, In step 5, the air source side circulating pump control instruction output is 0Hz by default.

6. The method of claim 1, wherein, The load optimization scheduling distribution method realizes semantic logic conversion through the ladder diagram language of the self-controllable programmable logic controller (PLC), and realizes process control on the process through the analog output (AO) and digital output (DO) channels of the controller. 7.An electronic device comprising a memory and a processor, the memory storing a computer program, wherein, The processor executes the computer program to realize the steps of the method in any one of claims 1-6.

8. A computer readable storage medium for storing computer instructions, characterized in that, The computer instructions are executed by the processor to realize the steps of the method in any one of claims 1-6.

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