Multi-heat-source collaborative heat supply energy gradient utilization optimization method

Abstract

The invention provides a multi-heat-source collaborative heat supply energy gradient utilization optimization method. Four energy supply forms of a heat supply secondary network, a ground source, a water source and an air source are combined in order, a multi-heat-source energy cascade control method based on a heat load demand gap and a multi-energy heat supply control system based on an autonomous controllable hardware architecture are established, multi-stage optimization utilization of heat supply energy is achieved, the degree of dependence on a single heat source is reduced to the maximum extent, and the heat supply efficiency is improved. Diversification of a heat supply carrier is remarkably improved, and a new mode of clean energy heat supply is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of multi-energy complementary integrated energy application, and in particular relates to a multi-heat source coordinated heating energy cascade utilization optimization method. Background Art

[0002] The optimization control technology of multi-energy complementary integrated energy system is a key technology to break the existing pattern of separate planning, design and operation of each energy supply and utilization system, and to achieve multi-energy synergy and complementary and stable operation of the integrated energy system. It aims to achieve efficient energy utilization and renewable energy consumption, and organically coordinates energy production, transmission and distribution, utilization and other links to achieve optimal system energy efficiency.

[0003] At this stage, multiple types of energy are restricted by their inherent characteristics and cannot form efficient energy utilization. At the same time, the energy within the system lacks comprehensive optimization thinking on cascade utilization, and it is impossible to effectively implement the development vision of clean, efficient and low-carbon.

[0004] In summary, in order to achieve flexible consumption of multiple types of energy and advocate efficient use of clean energy, more in-depth technical integration research is needed on multi-energy coupling control systems. Summary of the invention

[0005] The purpose of the present invention is to solve the problems in the prior art and propose a multi-heat source coordinated heating energy cascade utilization optimization method.

[0006] The present invention is implemented by the following technical scheme. The present invention proposes a multi-heat source coordinated heating energy cascade utilization optimization method, which includes the following steps:

[0007] Step 1: The controller self-checks and resets all devices, that is, all subsystem pumps and electric actuators are adjusted to the closed state;

[0008] Step 2: All equipment meets the start-up permission status, and the secondary network system auxiliary equipment, return water electric actuator, inlet water electric actuator, and secondary network circulation pump are started in sequence;

[0009] Step 3: All secondary network equipment operation or start-up signal feedback is accurate, and the ground source system auxiliary equipment, return water electric actuator, water inlet electric actuator, and ground source side circulation pump are started in sequence;

[0010] Step 4: All ground source equipment operation or start-up signal feedback is accurate, and the water source system auxiliary equipment, return water electric actuator, water inlet electric actuator, and water source circulation pump are started in sequence;

[0011] Step 5: All water source equipment operation or start-up signal feedback is accurate, and the air source system auxiliary equipment, return water electric actuator, water inlet electric actuator, and air source side circulation pump are started in sequence;

[0012] Step 6: All air source equipment operation or startup signal feedback is accurate, and the controller now seeks the best solution based on the heat load demand;

[0013] Step 7: After the startup sequence is completed, the power distribution of the multi-energy heating control system after startup is optimized and adjusted using the load optimization scheduling and distribution method;

[0014] Step 8: The multi-energy heating control system automatically stops the sequence, and stops the air source, water source, and ground source units in sequence. First, close the unit's return water electric actuator, then close the water inlet electric actuator, and finally shut down the unit. If the above unit is not started, skip the part of stopping the unit.

[0015] Furthermore, in step 2, the secondary network circulation pump control instruction output defaults to 25 Hz.

[0016] Furthermore, in step 3, the control instruction output of the ground source side circulation pump defaults to 0 Hz.

[0017] Furthermore, in step 4, the water source circulation pump control instruction output defaults to 0 Hz.

[0018] Furthermore, in step 5, the air source side circulation pump control instruction output defaults to 0 Hz.

[0019] Furthermore, the load optimization scheduling and allocation method is specifically as follows:

[0020] Step 1: Regularly collect the water supply of the heating secondary network, the return water of the secondary network and the outdoor ambient temperature, with a sampling interval of 5s;

[0021] Step 2: Periodically calculate the heating capacity of the secondary heating network, ground source, water source and air source. The cycle time is 5s. Define the instantaneous time t. The heating capacity of each subsystem is calculated by the following formula: 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 time T is 0, the heating capacity at time T is 0, and the heating capacity will not be negative, that is, the heating system will not absorb heat from the heating network;

[0022] Step 3: Under the premise that the four heating subsystems of the heating secondary network, ground source, water source, and air source are all in good condition, the energy supply mode is selected by default as the heating secondary network mode, which is marked as X1. The other modes are marked as ground source X2, water source X3, and air source X4. Define the energy consumption penalty factor Z. The larger the Z value, 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 4: Define the heat user demand as a fixed value. When the indoor ambient temperature changes, the heat user load demand is determined by the following formula:

[0024] Step 5: According to the target constraint condition of the multi-energy heating control system with the lowest energy consumption, the load power distribution target is optimized. The instantaneous control command outputs of each subsystem are P X1 , P X2 , P X3 , P X4 , when the optimization result is P Xi When it is 0, it means that the above subsystem does not need to be started, and the digital output DO output corresponding to its control instruction is set to 0; when the optimization result is P Xi When it is greater than 0, it means that the output should reach 100*P of the rated power. Xi %.

[0025] Furthermore, the target constraint conditions are specifically:

[0026]

[0027] Furthermore, the load optimization scheduling and distribution method completes semantic logic conversion through the ladder diagram language of the autonomous and controllable programmable logic controller PLC, and realizes process control of the process flow through the analog output AO and digital output DO channels of the controller.

[0028] The present invention proposes an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method for optimizing the cascade utilization of heating energy by coordinating multiple heat sources are implemented.

[0029] The present invention proposes a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of a method for optimizing the cascade utilization of heating energy by coordinating multiple heat sources.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The present invention provides a multi-heat source coordinated heating energy cascade utilization optimization method. The method is a heating energy cascade utilization optimization method implemented by a multi-energy heating control system based on an autonomous and controllable hardware architecture. The method minimizes the degree of dependence on a single heat source, significantly improves the diversification of heating carriers, and realizes a new clean energy heating model. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0033] Figure 1 The present invention is a flow chart of a method for optimizing the cascade utilization of heating energy by coordinating multiple heat sources. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] Combination Figure 1 The present invention proposes a multi-heat source coordinated heating energy cascade utilization optimization method, the method comprising the following steps:

[0036] Step 1: The controller self-checks and resets all devices, that is, all subsystem pumps and electric actuators are adjusted to the closed state;

[0037] Step 2: All equipment meets the start-up permission status, and the secondary network system auxiliary equipment, return water electric actuator, inlet water electric actuator, and secondary network circulation pump are started in sequence; in step 2, the secondary network circulation pump control command output defaults to 25Hz.

[0038] Step 3: All secondary network equipment operation or start-up signal feedback is accurate, and the ground source system ancillary equipment, return water electric actuator, water inlet electric actuator, and ground source side circulation pump are started in sequence; in step 3, the ground source side circulation pump control command output defaults to 0Hz.

[0039] Step 4: All ground source equipment operation or start-up signal feedback is accurate, and the water source system ancillary equipment, return water electric actuator, water inlet electric actuator, and water source circulation pump are started in sequence; in step 4, the water source circulation pump control command output defaults to 0Hz.

[0040] Step 5: When the operation or start-up signal feedback of all water source equipment is accurate, the air source system ancillary equipment, return water electric actuator, water inlet electric actuator, and air source side circulation pump are started in sequence; in step 5, the air source side circulation pump control command output defaults to 0Hz.

[0041] Step 6: All air source equipment operation or startup signal feedback is accurate, and the controller now seeks the best solution based on the heat load demand;

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

[0043] Step 8: The multi-energy heating control system automatically stops the sequence, and stops the air source, water source, and ground source units in sequence. First, close the unit's return water electric actuator, then close the water inlet electric actuator, and finally shut down the unit. If the above unit is not started, skip the part of stopping the unit.

[0044] The load optimization dispatching and allocation method is specifically as follows:

[0045] Step 1: Regularly collect the water supply of the heating secondary network, the return water of the secondary network and the outdoor ambient temperature, with a sampling interval of 5s;

[0046] Step 2: Periodically calculate the heating capacity of the secondary heating network, ground source, water source and air source. The cycle time is 5s. Define the instantaneous time t. 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 time T is 0, the heating capacity at time T is 0, and the heating capacity will not be negative, that is, the heating system will not absorb heat from the heating network;

[0047] Step 3: Under the premise that the four heating subsystems of the heating secondary network, ground source, water source, and air source are all in good condition, the energy supply mode is selected by default as the heating secondary network mode, which is marked as X1. The other modes are marked as ground source X2, water source X3, and air source X4. Define the energy consumption penalty factor Z. The larger the Z value, 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. When the indoor ambient temperature changes, the heat user load demand is determined by the following formula:

[0049] Step 5: According to the target constraint condition of the multi-energy heating control system with the lowest energy consumption, the load power distribution target is optimized. The instantaneous control command outputs of each subsystem are P X1 , P X2 , P X3 , P X4, when the optimization result is P Xi When it is 0, it means that the above subsystem does not need to be started, and the digital output DO output corresponding to its control instruction is set to 0; when the optimization result is P Xi When it is greater than 0, it means that the output should reach 100*P of the rated power. Xi %.

[0050] The target constraints are specifically:

[0051]

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

[0053] The present invention proposes a method for optimizing the cascade utilization of heating energy with the coordination of multiple heat sources. By orderly combining the four energy supply forms of the heating secondary network, ground source, water source and air source, a multi-heat source energy cascade control method based on the heat load demand gap is established. Based on the multi-energy heating control system with autonomous and controllable hardware architecture, multi-level optimal utilization of heating energy is achieved, the dependence on a single heat source is minimized, the diversification of heating carriers is significantly improved, and a new model of clean energy heating is realized.

[0054] The present invention proposes an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method for optimizing the cascade utilization of heating energy by coordinating multiple heat sources are implemented.

[0055] The present invention proposes a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of a method for optimizing the cascade utilization of heating energy by coordinating multiple heat sources.

[0056] The memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DRRAM). It should be noted that the memory of the method described in the present invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0057] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part 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, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may 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 may be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a high-density digital video disc (DVD)), or a semiconductor medium (eg, a solid state disc (SSD)).

[0058] In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software. The steps of the method disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor for execution, or a combination of hardware and software modules in a processor for execution. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it is not described in detail here.

[0059] It should be noted that the processor in the embodiment of the present application can be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiment can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor can be 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, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiment of the present application can be directly embodied as a hardware decoding processor to perform, or the hardware and software modules in the decoding processor can be combined and performed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0060] The above is a detailed introduction to the multi-heat source coordinated heating energy cascade utilization optimization method proposed in the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A multi-heat source coordinated heating energy cascade utilization optimization method, characterized in that: The method comprises the following steps: Step 1: The controller self-checks and resets all devices, that is, all subsystem pumps and electric actuators are adjusted to the closed state; Step 2: All equipment meets the start-up permission status, and the secondary network system auxiliary equipment, return water electric actuator, inlet water electric actuator, and secondary network circulation pump are started in sequence; Step 3: All secondary network equipment operation or start-up signal feedback is accurate, and the ground source system auxiliary equipment, return water electric actuator, water inlet electric actuator, and ground source side circulation pump are started in sequence; Step 4: All ground source equipment operation or start-up signal feedback is accurate, and the water source system auxiliary equipment, return water electric actuator, water inlet electric actuator, and water source circulation pump are started in sequence; Step 5: All water source equipment operation or start-up signal feedback is accurate, and the air source system auxiliary equipment, return water electric actuator, water inlet electric actuator, and air source side circulation pump are started in sequence; Step 6: All air source equipment operation or startup signal feedback is accurate, and the controller now seeks the best solution based on the heat load demand; Step 7: After the startup sequence is completed, the power distribution of the multi-energy heating control system after startup is optimized and adjusted using the load optimization scheduling and distribution method; Step 8: The multi-energy heating control system automatically stops the sequence, and stops the air source, water source, and ground source units in sequence. First, close the unit's return water electric actuator, then close the water inlet electric actuator, and finally shut down the unit. If the above unit is not started, skip the part of stopping the unit.

2. The method according to claim 1, characterized in that In step 2, the secondary network circulation pump control command output defaults to 25Hz.

3. The method according to claim 1, characterized in that In step 3, the control command output of the ground source side circulation pump defaults to 0 Hz.

4. The method according to claim 1, characterized in that: In step 4, the water source circulation pump control command output defaults to 0 Hz.

5. The method according to claim 1, characterized in that In step 5, the air source side circulation pump control command output defaults to 0 Hz.

6. The method according to claim 1, characterized in that The load optimization dispatching and allocation method is specifically as follows: Step 1: Regularly collect the water supply of the heating secondary network, the return water of the secondary network and the outdoor ambient temperature, with a sampling interval of 5s; Step 2: Periodically calculate the heating capacity of the secondary heating network, ground source, water source and air source. The cycle time is 5s. Define the instantaneous time t. The heating capacity of each subsystem is calculated by the following formula: θ 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 t时刻瞬时流量 , when the instantaneous flow at time T is 0, the heating capacity at time T is 0, and the heating capacity will not be negative, that is, the heating system will not absorb heat from the heating network; Step 3: Under the premise that the four heating subsystems of the heating secondary network, ground source, water source, and air source are all in good condition, the energy supply mode is selected by default as the heating secondary network mode, which is marked as X1. The other modes are marked as ground source X2, water source X3, and air source X4. Define the energy consumption penalty factor Z. The larger the Z value, 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; Step 4: Define the heat user demand as a fixed value. When the indoor ambient temperature changes, the heat user load demand is determined by the following formula: Step 5: According to the target constraint condition of the multi-energy heating control system with the lowest energy consumption, the load power distribution target is optimized. The instantaneous control command outputs of each subsystem are P X1 , P X2 , P X3 , P X4 , when the optimization result is P Xi When it is 0, it means that the above subsystem does not need to be started, and the digital output DO output corresponding to its control instruction is set to 0; when the optimization result is P Xi When it is greater than 0, it means that the output should reach 100*P of the rated power. Xi %.

7. The method according to claim 6, characterized in that The target constraints are specifically:

8. The method according to claim 6, characterized in that The load optimization scheduling and distribution method completes semantic logic conversion through the ladder diagram language of the autonomous controllable programmable logic controller PLC, and realizes process control of the process flow through the analog output AO and digital output DO channels of the controller.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium for storing computer instructions, characterized in that: When the computer instructions are executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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