A source side multi-energy station and net side joint energy storage collaborative optimization method, system, terminal and medium

Abstract

The application relates to the technical field of regional energy, and discloses a source-side multi-energy station and network-side joint energy storage collaborative optimization method, system, terminal and medium, the method comprising the following steps: determining a total cooling capacity prediction value of a regional cooling supply system in the next day and configuration parameters of the regional cooling supply system; according to the total cooling capacity prediction value and the configuration parameters, matching the operation mode of the regional cooling supply system step by step, determining a target operation mode and corresponding distribution information; if the target operation mode is a single-station base-loaded pipe network mode, a multi-station base-loaded pipe network mode or a double-working-condition main machine air conditioner working condition mode, determining a target energy station in the regional cooling supply system, and matching a cold storage pipe section and / or a water storage pool of the target energy station to carry out cold storage; if the target operation mode is a full-station water storage cooling mode or an ice storage water storage cooling mode, starting all energy stations of the regional cooling supply system according to the distribution information, and carrying out pipe network cold storage and water storage pool ice storage or cold storage. The application can improve the energy efficiency of the main machine operation and reduce the cost.

Description

Technical Field

[0001] This application relates to the field of regional energy technology, and in particular to a collaborative optimization method, system, terminal and medium for source-side multi-energy station and grid-side joint energy storage. Background Technology

[0002] District cooling systems are typically designed with cold storage systems, such as ice storage or water storage systems, to alleviate peak-valley differences in cooling load and reduce operating costs. However, these storage methods are all concentrated on the source side (refrigeration station) and do not consider the sensible heat storage potential of the distribution network itself. Taking ice storage systems as an example, their designed operation involves making ice and storing cold during off-peak hours at night and melting ice and releasing cold during peak hours in the daytime. Because the dual-mode refrigeration unit needs to operate continuously in ice-making mode for extended periods, the operating efficiency of the dual-mode refrigeration unit is generally low. Furthermore, due to the limited capacity of the ice storage tank, the amount of cold energy that a district cooling system energy station can store during off-peak hours is limited. Although related technologies utilize water within the district cooling system's distribution network as a sensible heat storage medium to improve operating efficiency and the overall system's cold storage capacity...

[0003] The relevant technologies overlook the fact that in district cooling system energy stations, refrigeration equipment can be divided into dual-mode chillers and base-load chillers according to their functions and operating conditions. During off-peak electricity hours at night, dual-mode chillers are responsible for ice storage in the ice storage tank, while base-load chillers handle sporadic loads in the pipe network. If the base-load chiller is shut down, the hourly cooling capacity of the dual-mode chiller remains essentially constant. Simply using the pipe network as a cold storage medium does not expand the system's cold storage capacity; instead, it wastes the available cooling capacity of the base-load chiller during off-peak hours, resulting in underutilization of the overall system cooling output during this period and a decrease in cold storage capacity instead of an increase.

[0004] Therefore, existing technologies still need to be improved and developed. Summary of the Invention

[0005] The main purpose of this application is to provide a collaborative optimization method, system, terminal and medium for source-side multi-energy station and grid-side joint energy storage. It aims to solve the problems in the existing technology where source-side cold storage only uses dual-mode main unit ice production during off-peak electricity hours at night, only uses the pipeline network as an energy storage medium without allowing the base load main unit to work simultaneously to produce cold, resulting in unused production capacity. Furthermore, it only focuses on a single cold station without coordinating multiple cold stations, leading to low operating energy efficiency and high cost of the cold storage system.

[0006] The first aspect of this application provides a collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage, the collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage including the following steps: Determine the predicted total cooling capacity of the district cooling system for the next day and the configuration parameters of the district cooling system; Based on the predicted total cooling capacity and the configuration parameters, the operation mode of the district cooling system is matched step by step to determine the target operation mode and the corresponding allocation information. The target operation mode is one of the following: single-station base load network mode, multi-station base load network mode, dual-condition main air conditioning mode, whole-station water storage mode, and ice storage water storage mode. If the target operating mode is a single-station base load network mode, a multi-station base load network mode, or a dual-condition main air conditioning mode, then the target energy station in the district cooling system is determined according to the total cooling capacity prediction value and the allocation information, and the cold storage pipe section and / or water storage tank of the target energy station are matched for cold storage. If the target operating mode is a whole-station water storage mode or an ice storage / water storage mode, then all energy stations in the regional cooling system are activated according to the allocation information to store cold in the pipeline network and ice or cold in the water storage tank.

[0007] Optionally, in one embodiment of this application, determining the predicted total cooling capacity of the district cooling system for the next day specifically includes: Obtain historical data and external influencing factors; Input the historical data and external influencing factors into the load forecasting model, and output the initial total cooling demand value for the next day; The comparison deviation is obtained by comparing the initial total cooling demand value with the actual operating load trend. If the comparison deviation is within the set threshold range, the initial total cooling demand value will be used as the predicted total cooling capacity value. If the comparison deviation exceeds the set threshold, the initial total cooling demand value is updated according to the actual operating load trend to determine the total cooling forecast value, wherein the total cooling forecast value is the total cooling capacity completed by the district cooling system during the off-peak electricity period.

[0008] Optionally, in one embodiment of this application, the configuration parameters include the base-load host capacity of each single station, the maximum cold storage capacity of the pipeline network covered by each single station, the air conditioning capacity of each single station under dual operating conditions, the total water storage capacity of the system, and the maximum water storage capacity of the system. The allocation information includes a candidate shutdown list of energy stations, key parameters, and output instructions. The step of matching the operating modes of the district cooling system step by step according to the predicted total cooling capacity and the configuration parameters to determine the target operating mode and corresponding allocation information specifically includes: If the predicted total cooling capacity is less than or equal to the single-station base load host capacity, and the predicted total cooling capacity is less than or equal to the maximum cold storage capacity of the pipeline network covered by the corresponding single station, then the target operating mode is determined to be the single-station base load pipeline network mode, and a candidate shutdown list and corresponding key parameters of the energy station are generated. When the target operating mode does not meet the single-station base load network mode, if the total cooling capacity prediction value is less than or equal to the total capacity of all the single-station base load main units, then the target operating mode is determined to be the multi-station base load network mode, and a candidate shutdown list and corresponding key parameters of the energy station are generated. When the target operating mode does not meet the multi-station base load network mode, if the total cooling capacity prediction value is less than or equal to the sum of the total cooling capacity of all the single-station base load host production capacity and the single-station dual-condition host air conditioning production capacity, then the target operating mode is determined to be the dual-condition host air conditioning mode, and a candidate shutdown list and corresponding key parameters of the energy station are generated. When the target operating mode does not meet the dual-condition host air conditioning operating mode, if the predicted total cooling capacity is less than or equal to the total water storage cooling capacity of the system, and the predicted total cooling capacity is less than or equal to the maximum water storage cooling capacity of the system, then the target operating mode is determined to be the whole-station water storage cooling mode, and the corresponding output command is generated. If the target operating mode does not meet the requirements of the whole-station water storage cooling mode, then the target operating mode is determined to be the ice storage cooling water storage cooling mode, and the corresponding output command is generated.

[0009] Optionally, in one embodiment of this application, if the target operating mode is a single-station base load network mode, a multi-station base load network mode, or a dual-condition main unit air conditioning mode, then determining the target energy station in the district cooling system based on the total cooling capacity prediction value and the allocation information specifically includes: If the target operating mode is a single-station base load network mode, a multi-station base load network mode, or a dual-condition main unit air conditioning mode, then an optimization problem model is constructed based on the total cooling capacity prediction value, the corresponding candidate shutdown list, and the key parameters, and the initial value of the state array is planned based on the optimization problem model. The target value of the state array is obtained by iterative optimization based on the initial value of the state array and the key parameters corresponding to the candidate shutdown list. The target energy station to be optimally retained and operated is determined based on the target value of the state array.

[0010] Optionally, in one embodiment of this application, the step of iteratively optimizing the state array based on the initial value of the state array and the key parameters corresponding to the candidate shutdown list to obtain the target value of the state array specifically includes: Based on the initial value of the state array and the key parameters corresponding to the candidate shutdown list, traverse each candidate energy station in the candidate shutdown list, and traverse the maximum total cold storage capacity and transformer capacity of each candidate energy station; Based on all the maximum total cold storage capacity and the corresponding transformer capacity, a target value for the state data is determined, wherein the target value for the state array is the sum of the minimum transformer capacities required for the total cold storage capacity.

[0011] Optionally, in one embodiment of this application, the matching of the cold storage pipe section of the target energy station specifically refers to: Based on the predicted total cooling capacity and the cold storage capacity of each pipe segment in the target energy station, task matching and pipe segment selection are performed to obtain a pairing relationship table between the energy station and the target pipe segment, and the valve opening and closing command for each cold storage loop is determined according to the pairing relationship table.

[0012] Optionally, in one embodiment of this application, if the target operating mode is a whole-station water storage mode or an ice storage / water storage mode, then according to the allocation information, all energy stations in the district cooling system are activated to store cold in the pipeline network and store ice or cold in the water storage tank, specifically including: If the target operating mode is the whole-station water storage mode, then according to the output command corresponding to the whole-station water storage mode, start all base load hosts of all energy stations in the district cooling system to operate and all dual-condition hosts to operate in air conditioning mode, and store cold in the pipeline network and the water storage tank. If the target operating mode is ice storage and water storage mode, then according to the output command corresponding to the ice storage and water storage mode, all base load hosts of all energy stations in the district cooling system are started to operate and all dual-mode hosts are started to operate in ice-making mode to store cold in the pipeline network and store ice in the water tank.

[0013] A second aspect of this application also provides a collaborative optimization system for source-side multi-energy stations and grid-side joint energy storage, wherein the collaborative optimization system for source-side multi-energy stations and grid-side joint energy storage is used to implement the collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage as described in any of the above schemes; the collaborative optimization system for source-side multi-energy stations and grid-side joint energy storage includes: The cooling forecast and parameter determination module is used to determine the total cooling capacity forecast of the district cooling system for the next day and the configuration parameters of the district cooling system. The operation mode determination module is used to match the operation mode of the regional cooling system step by step according to the total cooling capacity prediction value and the configuration parameters, and determine the target operation mode and the corresponding allocation information. The target operation mode is one of the following: single-station base load network mode, multi-station base load network mode, dual-condition main air conditioning mode, whole-station water storage mode, and ice storage water storage mode. The energy station shutdown and pipeline selection module is used to determine the target energy station in the district cooling system based on the total cooling capacity prediction value and the allocation information if the target operation mode is a single-station base load pipeline network mode, a multi-station base load pipeline network mode or a dual-condition host air conditioning mode, and to match the cold storage pipeline section and / or water storage tank of the target energy station for cold storage. The whole-station operation module is used to start all energy stations in the regional cooling system according to the allocation information if the target operation mode is whole-station water storage mode or ice storage water storage mode, and to store ice or cold in the pipeline network and water tank.

[0014] A third aspect of this application also provides a terminal, wherein the terminal includes: a memory, a processor, and a collaborative optimization program for source-side multi-energy station and grid-side joint energy storage stored in the memory and executable on the processor, wherein when the collaborative optimization program for source-side multi-energy station and grid-side joint energy storage is executed by the processor, it implements the steps of the collaborative optimization method for source-side multi-energy station and grid-side joint energy storage as described above.

[0015] A fourth aspect of this application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a collaborative optimization program for source-side multi-energy station and grid-side joint energy storage, and when the collaborative optimization program for source-side multi-energy station and grid-side joint energy storage is executed by a processor, it implements the steps of the collaborative optimization method for source-side multi-energy station and grid-side joint energy storage as described above.

[0016] Beneficial effects: This application provides a collaborative optimization method, system, terminal and medium for source-side multi-energy station and grid-side joint energy storage. By operating the ice storage system in water storage mode during low-load seasons, this application improves the main unit's energy efficiency and makes full use of the idle capacity of the base load main unit, thereby truly expanding the actual cold storage capacity of the system. By cross-site energy storage and dynamically shutting down the transformers of some energy stations, the system's capacity electricity expenditure is reduced. Furthermore, by dynamically matching the capacity of the cold storage network, ineffective cooling of excess networks is avoided, thereby reducing the overall cold loss of the system. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the district cooling system of this application; Figure 2This is a schematic diagram of the energy station in the district cooling system of this application; Figure 3 A flowchart illustrating a preferred embodiment of the collaborative optimization method for source-side multi-energy station and grid-side joint energy storage in this application; Figure 4 This is a schematic diagram of Mode 1 operation in a preferred embodiment of the collaborative optimization method for source-side multi-energy station and grid-side joint energy storage in this application; Figure 5 This is a schematic diagram of mode 2 operation in a preferred embodiment of the collaborative optimization method for source-side multi-energy station and grid-side joint energy storage in this application; Figure 6 This is a schematic diagram of mode 3 in a preferred embodiment of the collaborative optimization method for source-side multi-energy station and grid-side joint energy storage in this application; Figure 7 This is a schematic diagram of mode 4 in a preferred embodiment of the collaborative optimization method for source-side multi-energy station and grid-side joint energy storage in this application; Figure 8 This is a schematic diagram of mode 5 in a preferred embodiment of the collaborative optimization method for source-side multi-energy station and grid-side joint energy storage in this application; Figure 9 This is a flowchart illustrating the specific implementation steps for selecting cold storage pipe sections in a preferred embodiment of the collaborative optimization method for source-side multi-energy station and grid-side joint energy storage in this application. Figure 10 This is a structural diagram of a preferred embodiment of the collaborative optimization system for source-side multi-energy stations and grid-side joint energy storage in this application; Figure 11 This is a structural diagram of a preferred embodiment of the terminal of this application.

[0019] Explanation of reference numerals in the attached figures: 100. Cooling forecast and parameter determination module; 200. Operation mode determination module; 300. Energy station shutdown and pipeline selection module; 400. Overall station operation module. Detailed Implementation

[0020] To make the objectives, technical solutions, and effects of this application clearer and more explicit, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. The described embodiments are only possible technical implementations of this application and not all possible implementations. Based on the embodiments in this application, those skilled in the art can obtain other embodiments without creative effort, and these embodiments are also within the protection scope of this application.

[0021] The related technologies for cold storage in pipe networks and the cold water flow paths all have flaws. One proposed technology utilizes the fire water tanks of cooling customers as cold storage and bypass paths. However, current domestic design codes explicitly prohibit the use of fire water tanks for cold storage or bypass in cooling systems. This approach is only theoretically feasible but not practically feasible in engineering. Furthermore, even if future policies and regulations allow the use of fire water tanks for cold storage, the lack of insulation in these tanks would significantly increase system cold loss, making it economically unfeasible. Another proposed technology involves adding an extra return pipe, designing the entire district cooling system with one supply pipe and two return pipes. While technically feasible, this would greatly increase pipe network construction costs and system complexity. Additionally, the added return pipe would increase overall system cold loss by approximately 50%, making it uneconomical both in terms of initial investment and operational efficiency. A third proposed technology directly utilizes the heat exchange equipment of district cooling customers as a bypass. This solution is theoretically feasible but practically impractical. The reason for this is that current user metering instruments are generally installed at the front end of heat exchange equipment. Although bypassing the heat exchange equipment theoretically will not increase billing, in actual operation, due to the accumulation of errors in the metering instruments and the fluctuation of the operating conditions of the user-side heat exchange equipment, the metering deviation is easily amplified, leading to disputes over cooling services. Therefore, this method has been widely abandoned in engineering practice.

[0022] Furthermore, the relevant technologies do not consider the energy storage scheduling conflict problem when multiple energy stations operate collaboratively in a district cooling system. Although the relevant technologies propose multiple production capacity devices in the pipeline network, they do not clearly define the scheduling logic and coordination mechanism of energy storage nodes, nor do they provide dynamic priority determination rules for energy storage nodes such as load allocation among multiple energy stations and sharing of cold storage capacity, or collaborative scheduling strategies for cold storage capacity across energy stations.

[0023] All related technologies address the adaptability of energy storage strategies under the critical constraint of significant seasonal load variations in district cooling systems. These seasonal load differences make it difficult for a single energy storage strategy to maintain year-round operational efficiency. Furthermore, these technologies do not offer effective methods to reduce operating costs for district cooling energy stations during the lower-load winter and transitional seasons. While they increase the theoretical capacity of the energy storage system, they do not actually increase the daily actual cooling capacity (because not all capacity equipment is utilized), nor do they reduce capacity electricity costs for multiple energy stations (i.e., they do not actually reduce operating costs).

[0024] Related technologies only focus on a single cooling station and do not involve the coordinated operation of multiple cooling stations. Existing systems use multiple storage tanks, while this solution reduces capacity electricity costs and lowers overall costs by storing only one tank (e.g., storing only one tank with less heat dissipation).

[0025] In the attached diagram, the blue lines represent the cooling water supply pipes, and the yellow lines represent the return water pipes.

[0026] The following is a description of the terms used in the embodiments of this application: Refrigeration Unit: The main refrigeration equipment in a district cooling system. In ice storage projects, there are two types of refrigeration units. One type is the "dual-mode refrigeration unit," which, as the name suggests, has two operating modes: "ice-making mode," where the refrigeration temperature is typically -5 to -6°C, and the low-temperature refrigerant ethylene glycol is distributed to the ice storage coils to freeze the water in the pool into ice columns; and "air conditioning mode," where the refrigeration temperature is typically 3 to -6°C, and the low-temperature refrigerant ethylene glycol is distributed to the ethylene glycol heat exchanger to exchange heat with the high-temperature return water in the external pipe network. The other type is the "base-load refrigeration unit," which refers to the unit that performs refrigeration independently in the ice storage system without participating in ice making. The base-load refrigeration unit has only one operating mode: "air conditioning mode," where the refrigeration temperature is typically 3 to -6°C, and the low-temperature refrigerant is water, which is directly distributed to the cooling network.

[0027] Ice storage tank: In this application, the ice storage tank is used to store the cooling capacity generated by the refrigeration unit group during off-peak electricity hours at night, and to deliver the cooling capacity to users during other times of the day.

[0028] Ice storage coil: In traditional ice storage systems, this device is placed inside an ice storage tank. Under the "ice storage mode" of the dual-condition refrigeration unit, ethylene glycol, a low-temperature refrigerant at -5 to -6°C, is supplied to the ice storage coil, which is surrounded by water. Because the temperature of the low-temperature refrigerant ethylene glycol is below its freezing point, it freezes along the ice storage coil to form ice columns. Under this mode, approximately "tens of thousands of ice columns" will be frozen in the tank, which will contain an ice-water mixture. In this application, in addition to ice storage, this device is used to exchange heat with the tank during low-load seasons, lowering the water temperature in the tank to prepare a whole tank of low-temperature water.

[0029] Water distributor or water taker for ice storage tank: The water distributor or water taker is a special device in the ice storage system used to transfer high-temperature water from the ice tank / remove low-temperature water. It is usually placed on the end side of the ice tank.

[0030] Direct-supply heat exchanger: A heat exchange device used to transfer the cooling capacity generated by the refrigeration unit to the user's chilled water during refrigeration unit air conditioning operation. In this application, during the daytime when the user's air conditioning load is high, a portion of the refrigeration unit directly distributes cooling capacity to the direct-supply heat exchanger by closing the valve connected to the ice storage coil. There are two operating conditions for the direct-supply heat exchanger: one is that the chilled water only exchanges heat with the direct-supply heat exchanger, called the "direct-supply" mode; the other is that the chilled water first enters the direct-supply heat exchanger, changing from high-temperature water to medium-temperature water, and then the medium-temperature water enters the ice melting heat exchanger, changing to low-temperature water, called the "combined cooling" mode.

[0031] Water distributor: Used to distribute the flow of chilled water produced by the refrigeration station of the ice storage system according to the needs of different users.

[0032] Water collector: Used to collect high-temperature water returning from the pipeline network and distribute the flow according to the flow requirements of each piece of equipment in the ice storage cooling station.

[0033] Ethylene glycol pumps, cooling pumps, refrigeration pumps, and de-icing pumps: used for fluid distribution within various process subsystems.

[0034] Electric valves: used to switch the opening and closing status of various pipelines under different operating conditions.

[0035] In addition, the cost of the district cooling system will be explained: Commercial electricity usage differs from residential electricity usage. Commercial electricity users, in addition to settling their electricity bills based on actual monthly consumption, also need to pay a capacity charge based on the capacity of their transformers, known in the industry as a two-part tariff. For industrial and commercial users subject to a two-part tariff, the electricity bill consists of two parts: Total Electricity Bill = Electricity Cost (Price × Time Period) + Capacity Charge (Equipment Capacity × 22). Generally, the transformer capacity is 22 yuan / kVA·month. For example, if the equipment capacity is 10,000 kVA, then the monthly capacity charge would be 10,000 × 22 = 220,000 yuan. This application saves transformer capacity by strategically shutting down energy stations (under relevant policies, no corresponding capacity charge is required if the equipment is not used), thus saving costs (saving 220,000 yuan in capacity charges per month if 10,000 kVA is not used).

[0036] Electricity cost = Peak electricity cost (e.g., 1.2 yuan per kWh) + Average electricity cost (e.g., 0.7 yuan per kWh) + Off-peak electricity cost (e.g., 0.2 yuan per kWh) = Actual peak electricity consumption (kWh) × Peak electricity price (yuan / kWh) + Actual average electricity consumption (kWh) × Average electricity price (yuan / kWh) + Actual off-peak electricity consumption (kWh) × Off-peak electricity price (yuan / kWh).

[0037] Capacity charge = transformer capacity or maximum demand (kVA or kW) × capacity charge (yuan / kW / month). Simply put, it is paying for the power supply capacity used.

[0038] In layman's terms, even if a district cooling station doesn't use a single kilowatt-hour of electricity in a month, it still has to pay capacity charges. Typically, a single station pays hundreds of thousands of yuan in capacity charges each month. For example, in a certain district cooling system, each station might pay around 500,000 yuan in capacity charges per month. For cooling stations with low cooling loads, the revenue they sell to users may be less than the electricity they pay to the power company. In other words, without appropriate measures, they are essentially selling at a loss during low-load periods.

[0039] This application focuses on regional energy and HVAC systems, aiming to improve the energy efficiency of dual-mode chillers during off-peak hours and expand the overall cold storage capacity of the system. The collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage utilizes a coordinated start-stop strategy for source-side dual-mode chillers and base-load chillers during off-peak hours. This achieves the dual goals of improving the energy efficiency of source-side chillers and expanding cold storage capacity without adding return water pipes, causing metering disputes with users, or violating fire safety regulations. It simultaneously activates the high-efficiency operating potential of dual-mode chillers during off-peak hours and the redundant cooling capacity of base-load chillers. Furthermore, by reconstructing the grid-side sensible heat storage flow path and segmenting compliant, low-cost bypass branches between existing supply / return water mains, this application enables flexible adjustment and dynamic matching of energy storage capacity under different loads throughout the year. This significantly improves the system's adaptability to seasonal load fluctuations and minimizes overall system cooling losses. The multi-energy station collaborative energy storage strategy proposed in this application can realize cross-station energy storage dispatch, thereby achieving optimal economic efficiency in different seasons throughout the year.

[0040] The technical solutions of this application will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0041] First, the district cooling system in the embodiments of this application will be described: such as Figure 1 and Figure 2 As shown, a district cooling system consists of three parts: the district energy station on the source side, the cooling pipeline network on the grid side, and the users.

[0042] The regional energy station includes a dual-mode refrigeration unit, ethylene glycol pumps, ethylene glycol heat exchangers, cold storage equipment, an ice storage tank, ice melting pumps, a base-load refrigeration unit, a base-load chilled water pump, an external network pump, and auxiliary valves. The dual-mode refrigeration unit has two operating modes: one is to prepare an ethylene glycol solution below 0°C (freezing point) and distribute it to the ice storage tank for ice making; the other is to prepare an ethylene glycol solution above 0°C (freezing point), which, through an ethylene glycol heat exchanger, cools the high-temperature return water in the network return pipe to approximately 3°C, thereby delivering the cooling capacity to the network. The base-load refrigeration unit has only one operating mode: cooling the high-temperature return water in the network return pipe to approximately 3°C. The storage path for the cooling capacity prepared by the base-load unit varies depending on the season; it can be distributed to the low-temperature supply water pipe of the cooling network or the ice storage tank via connecting pipes and valves within the station.

[0043] The cooling network includes low-temperature water supply pipes, high-temperature return water pipes, bypass pipes, and auxiliary valves. Electric separation valves are installed at the connection points of the cooling network of different regional energy stations.

[0044] The user portion mainly includes the heat exchange room and the user's energy-consuming building body.

[0045] The preferred embodiment of this application describes a collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage, such as... Figure 3 As shown, the collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage includes the following steps: In step S10, the predicted total cooling capacity of the district cooling system for the next day and the configuration parameters of the district cooling system are determined.

[0046] In one possible implementation, step S10 specifically includes: acquiring historical data from the same period and external influencing factors; inputting the historical data from the same period and the external influencing factors into the load forecasting model, and outputting the initial total cooling demand value for the next day; comparing the initial total cooling demand value with the actual operating load trend to obtain the comparison deviation; if the comparison deviation is within a set threshold range, then using the initial total cooling demand value as the total cooling forecast value; if the comparison deviation exceeds the set threshold, then updating the initial total cooling demand value according to the actual operating load trend to determine the total cooling forecast value, wherein the total cooling forecast value is the total cooling capacity completed by the district cooling system during off-peak electricity periods.

[0047] Specifically, the data is input into an existing load forecasting model (which can be a time series model, a neural network model, etc.) to calculate a preliminary total cooling demand value for the next day; the calculation result is compared with the actual operating load trend of the previous day or the most recent period to determine whether the forecast value has an unreasonable deviation; if the deviation is too large, intervention and correction are carried out, such as using a rolling correction algorithm to integrate the latest actual operating data to update the forecast value, and finally outputting a determined total cooling demand forecast value for the next day.

[0048] In step S20, the operating modes of the district cooling system are matched step by step according to the predicted total cooling capacity and the configuration parameters to determine the target operating mode and corresponding allocation information. The target operating mode is a single-station base-load pipe network mode (Mode 1). Figure 4 Multi-station base-loaded pipeline network mode (Mode 2) Figure 4 ), dual-condition air conditioning unit operating mode (mode 3, Figure 5 ), whole-station water storage cooling mode (mode 4, Figure 6 ) and ice storage and chilled water storage modes (Mode 5, Figure 7 One of them.

[0049] In one possible implementation, the configuration parameters include the base-load host capacity of each individual station, the maximum cold storage capacity of the pipeline network covered by each individual station, the dual-condition air conditioning capacity of each individual station, the total water-based cold storage capacity of the system, and the maximum water-based cold storage capacity of the system. The allocation information includes a candidate shutdown list of energy stations, key parameters, and output instructions. Step S20 specifically includes: If the predicted total cooling capacity is less than or equal to the single-station base load host capacity, and the predicted total cooling capacity is less than or equal to the maximum cold storage capacity of the pipeline network covered by the corresponding single station, then the target operating mode is determined to be the single-station base load pipeline network mode, and a candidate shutdown list and corresponding key parameters of the energy station are generated. When the target operating mode does not meet the single-station base load network mode, if the total cooling capacity prediction value is less than or equal to the total capacity of all the single-station base load main units, then the target operating mode is determined to be the multi-station base load network mode, and a candidate shutdown list and corresponding key parameters of the energy station are generated. When the target operating mode does not meet the multi-station base load network mode, if the total cooling capacity prediction value is less than or equal to the sum of the total cooling capacity of all the single-station base load host production capacity and the single-station dual-condition host air conditioning production capacity, then the target operating mode is determined to be the dual-condition host air conditioning mode, and a candidate shutdown list and corresponding key parameters of the energy station are generated. When the target operating mode does not meet the dual-condition host air conditioning operating mode, if the predicted total cooling capacity is less than or equal to the total water storage cooling capacity of the system, and the predicted total cooling capacity is less than or equal to the maximum water storage cooling capacity of the system, then the target operating mode is determined to be the whole-station water storage cooling mode, and the corresponding output command is generated. If the target operating mode does not meet the requirements of the whole-station water storage cooling mode, then the target operating mode is determined to be the ice storage cooling water storage cooling mode, and the corresponding output command is generated.

[0050] It should be noted that: Maximum cold storage capacity of the pipeline network: the maximum sensible heat cold storage capacity that the transmission and distribution pipeline network can support under the premise of no additional return water and compliant bypass; Single-station base-load host capacity: the total cooling capacity of all base-load hosts in a single energy station during off-peak electricity hours; Total capacity of multi-station base-load hosts: the sum of the total cooling capacity of all base-load hosts that are not planned to be shut down during off-peak electricity hours; Single-station dual-mode host air conditioning mode capacity: the cooling capacity of dual-mode hosts under air conditioning mode (water-based cold storage); Total water-based cold storage capacity of the entire system: the sum of all base-load hosts of all energy stations and dual-mode hosts operating under air conditioning mode; Total ice-based cold storage capacity of the entire system: the maximum cooling capacity of all dual-mode hosts of all energy stations under ice-making mode; Maximum water-based cold storage capacity of the entire system: the upper limit of water-based cold storage capacity for all energy stations in combination with the pipeline network.

[0051] Specifically, see Figure 4According to Table 1, under the single-station base-load pipeline network mode (Mode 1): In winter, when the cooling load is extremely low, only a few base-load refrigeration units in the district cooling energy stations are used for pipeline water storage. The selection of the storage pipeline network volume and bypass route is determined based on the load forecast of the cooling system for the next day. Because this application dynamically configures the storage pipeline network volume to meet the load demand, the contact area between the storage medium and the environment can be significantly reduced, thereby reducing the cold loss of the storage system. Furthermore, the power distribution equipment of energy stations not participating in storage is proactively shut down during this season, thereby saving the operating costs of the entire district cooling system and reducing refrigeration costs. The selection method for the storage pipeline network volume and which energy stations to shut down is explained in step S30. In this mode, some energy stations are shut down, and the entire district cooling system is supplied only by cross-station energy storage from a few energy stations.

[0052] Table 1: Valve Opening / Closing Status under Mode 1 Operating Conditions

[0053] See Figure 5 According to Table 2, under the multi-station base load network mode (Mode 2): In winter when the cooling load is low, if the predicted load of the cooling system for the next day is greater than the maximum cold storage capacity of the cooling network, but less than the sum of the total cooling capacity of the base load chillers in the non-shutdown regional energy stations during off-peak electricity periods, in addition to using the cooling network as the cold storage medium, the ice storage water tank in the energy station also needs to be used as the cold storage medium. In this mode, only a few base load chillers in the regional cooling energy stations are still used for both station-based water cold storage and network water cold storage. This application utilizes the cold storage water tank of the original ice storage system in the form of water cold storage, so that the dual-condition chillers in the station do not need to operate in ice storage condition, which greatly improves the operating efficiency of the chillers. In addition, the power distribution equipment of the energy stations that do not participate in cold storage is actively shut down during this season, thereby saving the operating costs of the entire regional cooling system and reducing the cooling cost. The selection of the cold storage network volume and the selection method of which energy sources to shut down are explained in step S30. In this model, some energy stations are shut down, and the entire regional cooling system is supplied only by cross-station energy storage at a few energy stations.

[0054] Table 2: Valve Opening / Closing Status under Mode 2 Operating Conditions

[0055] See Figure 6According to Table 3, under the dual-condition air conditioning operating mode (Mode 3): In winter when the cooling load is low, if the predicted load of the cooling system for the next day is greater than the maximum cold storage capacity of the cooling network, greater than the sum of the total cooling capacity of the base-load chillers in the non-shutdown regional energy stations during off-peak electricity periods, and less than the sum of the total cooling capacity of the dual-condition chillers and base-load chillers in the non-shutdown regional energy stations during off-peak electricity periods, in addition to using the cooling network as the cold storage medium, the ice storage tank in the energy station also needs to be used as the cold storage medium. In this mode, a small number of dual-condition chillers in the regional cooling energy stations are used for water storage in the station's water tank, and the base-load chillers are used for water storage in the network. This application utilizes the cold storage tank of the original ice storage system in a "water storage" manner, so the dual-condition chillers in the station do not need to operate in ice storage mode, which greatly improves the operating efficiency of the chillers. During this season, the power distribution equipment of energy stations not involved in cold storage is proactively shut down, thereby saving operating costs and reducing refrigeration costs for the entire district cooling system. The selection of the cold storage network volume and the method for selecting which energy sources to shut down are explained in step S30. In this mode, some energy stations are shut down, and the entire district cooling system is supplied solely through cross-site energy storage at a few energy stations.

[0056] Table 3: Valve Opening / Closing Status under Mode 3 Operating Conditions

[0057] See Figure 7 According to Table 4, under the whole-station water-based cooling mode (Mode 4): During the transitional season when the cooling load is low, if the predicted load of the cooling system for the next day is greater than the maximum cooling capacity of the cooling network, less than the sum of the total cooling capacity of the dual-condition chillers and base-load chillers in all energy stations during off-peak electricity periods, and less than the maximum cooling capacity of the ice storage tanks in the cooling network and all energy stations operating in "water-based cooling" mode, then the dual-condition chillers in all regional energy stations will be activated for water-based cooling in the station's water tanks, and the base-load chillers will be activated for water-based cooling in the network. Under this mode, all energy stations must be operational, and the cooling network can be either connected to the network or isolated by closing the connecting valves.

[0058] Table 4: Valve Opening / Closing Status under Mode 4 Operating Conditions

[0059] See Figure 8According to Table 5, under the ice storage / water storage mode (Mode 5): During the transitional season and summer when the cooling load is high, if the predicted load of the cooling system for the next day exceeds the maximum cooling capacity of the ice storage tanks in the cooling network and all energy stations operating in "water storage" mode, the dual-condition chillers in all regional energy stations will be activated for ice storage, while the base load chillers will be activated for water storage in the network. In this mode, all energy stations must be operational. The cooling network can be either connected to the network or isolated by closing the connecting valves.

[0060] Table 5: Valve Opening / Closing Status under Mode 5 Operating Conditions

[0061] In step S30, if the target operating mode is a single-station base load network mode, a multi-station base load network mode, or a dual-condition main unit air conditioning mode, then the target energy station in the district cooling system is determined according to the total cooling capacity prediction value and the allocation information, and the cold storage pipe section and / or water storage tank of the target energy station are matched for cold storage.

[0062] In one possible implementation, step S30 specifically includes: if the target operating mode is a single-station base load network mode, a multi-station base load network mode, or a dual-condition main unit air conditioning mode, then an optimization problem model is constructed based on the predicted total cooling capacity, the corresponding candidate shutdown list, and the key parameters, and an initial value of the state array is planned based on the optimization problem model; iterative optimization is performed based on the initial value of the state array and the key parameters corresponding to the candidate shutdown list to obtain the target value of the state array; and the target energy station to be optimally retained for operation is determined based on the target value of the state array.

[0063] In one possible implementation, determining the target value of the state array is specifically achieved as follows: based on the initial value of the state array and the key parameters corresponding to the candidate shutdown list, traverse each candidate energy station in the candidate shutdown list, and traverse the maximum total cold storage capacity and transformer capacity of each candidate energy station; based on all the maximum total cold storage capacity and the corresponding transformer capacity, determine the target value of the state data, wherein the target value of the state array is the sum of the minimum transformer capacities required for the total cold storage capacity.

[0064] Specifically, in modes 1 to 3, some regional energy stations need to be shut down to optimize the overall system's economics. The question is how to choose which energy stations to shut down.

[0065] The following specific embodiments further illustrate step S30 of the above-mentioned collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage in this application: For multi-energy stations connected to the network, during seasons with low cooling loads, the power distribution facilities of several energy stations with low loads can be temporarily shut down by proactively reporting to the power department, and cross-station energy storage can be utilized to improve the economic efficiency of the entire regional cooling system.

[0066] The first step is to predict the maximum load day of the entire district cooling system for the month, and the total cooling capacity for that day. ; The second step is to determine... Is it greater than or equal to the sum of the maximum daily cooling capacity of N energy sources within the entire district cooling system? If so... If the sum of the maximum daily cold storage capacity of N energy sources is greater than or equal to the sum of the maximum daily cold storage capacity of N energy sources, then no energy station will be shut down. If If the sum of the maximum daily cold storage capacity of N energy sources is less than the sum of the maximum daily cold storage capacity of N energy sources, then proceed to the third step: select the most suitable energy station to shut down.

[0067] The third step, dynamic optimization, involves step S311, which is a dynamic optimization problem. This type of problem is a one-dimensional array combination optimization problem, where the relevant information of N energy stations is summarized into N one-dimensional arrays. , … Each array contains two elements: = ( , (), The first element represents the first element. i The maximum daily cold storage capacity of each energy station The second element represents the first element. i (Transformer capacity of each energy station). A subset needs to be selected. ,satisfy: Constraint: The sum of the first elements of all arrays in the subset , ( (This refers to the predicted total cooling capacity for the system on the day of maximum load in the current month). Optimization objective: The sum of the second elements of all arrays in the subset. The goal is to find a subset that meets the following criteria: minimum (i.e., the minimum sum of transformer capacities of the selected energy station combination, and the minimum capacity electricity cost for the entire system in the current month). .

[0068] The solution steps are as follows: Step S312, Dynamic Programming State Definition: definition This means: After selecting several arrays, the sum of the first elements is... When, the minimum value of the sum of the second element.

[0069] The range of values ​​for: ,in (The sum of the first element of all arrays, i.e., the maximum possible sum); (Infinity) indicates that it is impossible to make the sum of the first elements of the array equal to the sum of the first elements. ; Initial state: (The sum of the empty set is 0, and the sum of the second element is also 0).

[0070] Then, initialize. Array: Create a size of array Initialization rules:

[0071] in, Represent it with a sufficiently large number.

[0072] Step S313, state transition, fill in surface: For each array Update by traversing in reverse order To avoid repeatedly selecting the same array: Traversal order: Traverse each array in the outer loop. (from 1 to N ), inner layer from the maximum possible and Reverse traversal to (Right now j=S,S 1,..., State transition equation: If an array is selected Then the current and It can be composed of the previous one and Plus Received. Update with the minimum value: Either don't choose (reserve ), or choose (use renew).

[0073] Step S314: Find the optimal solution, which is the minimum sum of the second element: In all satisfied In the state, find the smallest That is, the sum of the second element of the optimal solution: The corresponding optimal sum ; ( It is the sum of the first elements at this point, satisfying... ).

[0074] Step S315, backtrack the selected array: By recording the source of each state, we can trace back which arrays were selected: Auxiliary recording: Two additional arrays are recorded when filling in the form: : to reach and The last selected array index ; : to reach and The previous one and (i.e.) Backtracking process: from optimal sum Begin, repeat the process: if (array) Selected), marked ;renew (Backtracking to the previous sum); Termination condition: (Return to empty set state). Output: Selected array collection. The sum of the first element (satisfy ); the sum of the second element (Minimum value).

[0075] In one possible implementation, matching the cold storage pipe section of the target energy station specifically involves: performing task matching and pipe section selection based on the predicted total cooling capacity and the cold storage capacity of each pipe section in the target energy station to obtain a pairing relationship table between the energy station and the target pipe section, and determining the valve switching command for each cold storage loop based on the pairing relationship table.

[0076] See Figure 9 In Mode 1, the volume of the cooling network to be put into cold storage and the bypass route need to be determined based on the load conditions. Specifically, the selection of the cooling network volume to minimize the overall system cooling loss includes: Step S321: First, based on the cooling capacity of the base-load refrigeration unit of the energy station that has not been actively shut down, renumber the dispatchable energy stations from largest to smallest.

[0077] Step S323: Predict the system cooling load for the next day. Q 0; Step S323: Determine the maximum cold storage capacity of the energy station with the maximum base load cooling capacity during the off-peak electricity period of the day. Q 1. Does it satisfy? Q 0; Step S324: If the conditions are met, only the first energy station is activated, and the corresponding cold storage pipe section is selected based on the predicted load. If the conditions are not met, a set of n energy stations is selected, ensuring that the total cold storage capacity of the n energy station sets meets the system cooling load for the next day. The cold storage capacity of each of the n energy stations is allocated according to their respective base load cooling capacity, and finally, the corresponding cold storage pipe section is selected based on the allocated cold storage capacity of each energy station.

[0078] In step S40, if the target operating mode is a whole-station water storage mode or an ice storage / water storage mode, then all energy stations in the district cooling system are activated according to the allocation information to store cold in the pipeline network and store ice or cold in the water storage tank.

[0079] Figure 9 The formula in the text is as follows: ; ; ; ; ; ; Wherein, 1 to N: are the numbers assigned to each refrigeration station based on the total cooling capacity of the refrigeration units equipped in each station; h: The return water pipe is numbered according to its distance from the cooling station. h-1 is the return water pipe section numbered 1, and hk is the return water pipe section numbered k. The cooling load (or total cooling capacity for the next day, in kWh) of the entire district cooling system that is connected to the network. : No. The total cooling capacity (or total cooling volume, in kWh) of an energy station throughout the day. This refers to the total cooling capacity of the first energy station throughout the day; Based on the cooling capacity of the base units configured in the n energy stations, the cold storage capacity of each energy station is allocated proportionally, where the cold storage capacity allocated to the i-th energy station is in kWh. The volume of the cooling medium stored in the return water pipe section numbered h, in cubic meters. 3 ; The volume of the cooling medium stored in the return water pipe section numbered j, in cubic meters. 3 ; : Average temperature of the cooling medium in the water supply pipe section of the numbered chiller station, in °C; The average temperature of the cooling medium stored in the return water pipe section numbered h, in °C; : The specific heat capacity at constant pressure of the cooling medium stored in the return water pipe section, expressed in kJ / kg·k; The density of the cooling medium stored in the return water pipe section, in kg / m³. 3 ; : No. Valves installed on the bypass pipe.

[0080] In one possible implementation, step S40 specifically includes: If the target operating mode is the whole-station water storage mode, then according to the output command corresponding to the whole-station water storage mode, start all base load hosts of all energy stations in the district cooling system to operate and all dual-condition hosts to operate in air conditioning mode, and store cold in the pipeline network and the water storage tank. If the target operating mode is ice storage and water storage mode, then according to the output command corresponding to the ice storage and water storage mode, all base load hosts of all energy stations in the district cooling system are started to operate and all dual-mode hosts are started to operate in ice-making mode to store cold in the pipeline network and store ice in the water tank.

[0081] It is understandable that this application can fully utilize the dual-condition chiller and base-load chiller in the district cooling system energy station to increase the cold storage capacity. Related technologies only focus on expanding the capacity of the cold storage system by taking into account the distribution medium (water) in the pipeline network and the cold storage medium (water) in the ice storage tank in the energy station. They do not take into account that the total cooling capacity of the dual-condition chiller is basically constant during off-peak electricity hours at night. Although the energy storage system capacity is expanded, the cold storage capacity is not expanded.

[0082] This application proposes a district cooling system where multiple energy stations are interconnected via a transmission and distribution network to achieve cross-station energy storage. Based on the load characteristics of different seasons throughout the year, a method is proposed to determine the number of energy stations to participate in energy storage during the winter and transitional seasons when loads are lower, according to the total load of all connected users. Cooling stations that do not require energy storage can proactively shut down their relevant transformer equipment during these seasons, thereby reducing capacity charges and improving the overall economic efficiency of the district cooling system.

[0083] This application enables the determination of a matching cold storage capacity based on the cooling demand of the district cooling system during the season. As the cold storage capacity increases, the heat exchange area in contact with the surrounding environment also increases, leading to greater cold loss. This application can reduce system cold loss during off-peak seasons, thereby improving the overall economic efficiency of the district cooling system.

[0084] This application maximizes the use of cold storage in the cooling supply and distribution network without adding a new return water pipe, causing metering disputes with users, or violating fire protection regulations, and also reduces costs. This application involves setting up a bypass pipeline of the same diameter and a matching electric valve before the user's metering point to ensure the compliance of the cold storage flow path in the network.

[0085] It should be noted that this application does not include a heat exchanger that physically isolates the ice storage tank from the pipe network. In the industry, systems with this type of heat exchanger are typically called closed-loop ice melting systems, while systems without it are typically called open-loop ice melting systems. The advantage of a closed-loop ice melting system is that the water in the ice storage tank is physically isolated from the water in the pipe network, allowing for control of system operating pressure, liquid level, and water quality. However, the disadvantage is that the presence of the heat exchanger reduces the system's heat exchange efficiency. The advantage of an open-loop ice melting system is its higher heat exchange efficiency due to the absence of the heat exchanger. However, the disadvantage is that control of system operating pressure, liquid level, and water quality is more difficult. In other words, this application can be modified from an open-loop ice melting system to a closed-loop ice melting system.

[0086] Furthermore, the accompanying drawings in this application only depict two energy stations, but are not limited to this; it may also depict a combined cold storage system of three, four, or more energy stations.

[0087] Next, referring to the accompanying drawings, a collaborative optimization system for source-side multi-energy stations and grid-side joint energy storage proposed according to the embodiments of this application is described, which is used to implement the collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage as described in any of the above schemes.

[0088] Figure 10 This is a structural diagram of the collaborative optimization system of source-side multi-energy stations and grid-side joint energy storage according to an embodiment of this application.

[0089] like Figure 10 As shown, the collaborative optimization system for source-side multi-energy stations and grid-side joint energy storage includes: a cooling prediction and parameter determination module 100, an operation mode determination module 200, an energy station shutdown and pipeline selection module 300, and a station-wide operation module 400.

[0090] Specifically, the cooling forecast and parameter determination module 100 is used to determine the predicted total cooling capacity of the district cooling system for the next day and the configuration parameters of the district cooling system. The operation mode determination module 200 is used to match the operation mode of the regional cooling system step by step according to the total cooling capacity prediction value and the configuration parameters, and determine the target operation mode and the corresponding allocation information. The target operation mode is one of the following: single-station base load network mode, multi-station base load network mode, dual-condition main air conditioning mode, whole-station water storage mode, and ice storage water storage mode. The energy station shutdown and pipeline selection module 300 is used to determine the target energy station in the district cooling system based on the total cooling capacity prediction value and the allocation information if the target operation mode is a single-station base load pipeline network mode, a multi-station base load pipeline network mode or a dual-condition host air conditioning mode, and to match the cold storage pipeline section and / or water storage tank of the target energy station for cold storage. The whole-station operation module 400 is used to start all energy stations in the regional cooling system according to the allocation information if the target operation mode is whole-station water storage mode or ice storage water storage mode, and to store ice or cold in the pipeline network and water tank.

[0091] Figure 11 A structural diagram of a terminal provided in an embodiment of this application. The terminal may include: The memory 501, the processor 502, and the computer program stored on the memory 501 and capable of running on the processor 502.

[0092] When the processor 502 executes the program, it implements the collaborative optimization method for source-side multi-energy station and grid-side joint energy storage provided in the above embodiments.

[0093] Furthermore, the terminal also includes: Communication interface 503 is used for communication between memory 501 and processor 502.

[0094] The memory 501 is used to store computer programs that can run on the processor 502.

[0095] Memory 501 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0096] If the memory 501, processor 502, and communication interface 503 are implemented independently, then the communication interface 503, memory 501, and processor 502 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EIS) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 11 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0097] Optionally, in a specific implementation, if the memory 501, processor 502, and communication interface 503 are integrated on a single chip, then the memory 501, processor 502, and communication interface 503 can communicate with each other through an internal interface.

[0098] Processor 502 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0099] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage.

[0100] One embodiment of this application provides a computer program product, including a computer program that, when executed by a processor, implements the features described in this application. Figure 1 The corresponding embodiments provide a collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage.

[0101] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0102] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0103] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0104] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable storage medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable storage medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable storage medium could be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0105] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0106] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0107] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0108] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

[0109] It should be understood that the application of this application is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage, characterized in that, The collaborative optimization method for source-side multi-energy station and grid-side joint energy storage includes: Determine the predicted total cooling capacity of the district cooling system for the next day and the configuration parameters of the district cooling system; Based on the predicted total cooling capacity and the configuration parameters, the operation mode of the district cooling system is matched step by step to determine the target operation mode and the corresponding allocation information. The target operation mode is one of the following: single-station base load network mode, multi-station base load network mode, dual-condition main air conditioning mode, whole-station water storage mode, and ice storage water storage mode. If the target operating mode is a single-station base load network mode, a multi-station base load network mode, or a dual-condition main air conditioning mode, then the target energy station in the district cooling system is determined according to the total cooling capacity prediction value and the allocation information, and the cold storage pipe section and / or water storage tank of the target energy station are matched for cold storage. If the target operating mode is a whole-station water storage mode or an ice storage / water storage mode, then all energy stations in the regional cooling system are activated according to the allocation information to store cold in the pipeline network and ice or cold in the water storage tank.

2. The collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage according to claim 1, characterized in that, The predicted total cooling capacity of the district cooling system for the next day specifically includes: Obtain historical data and external influencing factors; Input the historical data and external influencing factors into the load forecasting model, and output the initial total cooling demand value for the next day; The comparison deviation is obtained by comparing the initial total cooling demand value with the actual operating load trend. If the comparison deviation is within the set threshold range, the initial total cooling demand value will be used as the predicted total cooling capacity value. If the comparison deviation exceeds the set threshold, the initial total cooling demand value is updated according to the actual operating load trend to determine the total cooling forecast value, wherein the total cooling forecast value is the total cooling capacity completed by the district cooling system during the off-peak electricity period.

3. The collaborative optimization method for source-side multi-energy station and grid-side joint energy storage according to claim 1, characterized in that, The configuration parameters include the base load host capacity of each single station, the maximum cold storage capacity of the pipeline network covered by each single station, the dual-condition host air conditioning capacity of each single station, the total water storage capacity of the system, and the maximum water storage capacity of the system. The allocation information includes the candidate shutdown list of energy stations, key parameters, and output instructions. The step of matching the operating modes of the district cooling system step by step according to the predicted total cooling capacity and the configuration parameters to determine the target operating mode and corresponding allocation information specifically includes: If the predicted total cooling capacity is less than or equal to the single-station base load host capacity, and the predicted total cooling capacity is less than or equal to the maximum cold storage capacity of the pipeline network covered by the corresponding single station, then the target operating mode is determined to be the single-station base load pipeline network mode, and a candidate shutdown list and corresponding key parameters of the energy station are generated. When the target operating mode does not meet the single-station base load network mode, if the total cooling capacity prediction value is less than or equal to the total capacity of all the single-station base load main units, then the target operating mode is determined to be the multi-station base load network mode, and a candidate shutdown list and corresponding key parameters of the energy station are generated. When the target operating mode does not meet the multi-station base load network mode, if the total cooling capacity prediction value is less than or equal to the sum of the total cooling capacity of all the single-station base load host production capacity and the single-station dual-condition host air conditioning production capacity, then the target operating mode is determined to be the dual-condition host air conditioning mode, and a candidate shutdown list and corresponding key parameters of the energy station are generated. When the target operating mode does not meet the dual-condition host air conditioning operating mode, if the predicted total cooling capacity is less than or equal to the total water storage cooling capacity of the system, and the predicted total cooling capacity is less than or equal to the maximum water storage cooling capacity of the system, then the target operating mode is determined to be the whole-station water storage cooling mode, and the corresponding output command is generated. If the target operating mode does not meet the requirements of the whole-station water storage cooling mode, then the target operating mode is determined to be the ice storage cooling water storage cooling mode, and the corresponding output command is generated.

4. The collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage according to claim 3, characterized in that, If the target operating mode is a single-station base-load pipeline network mode, a multi-station base-load pipeline network mode, or a dual-condition main unit air conditioning mode, then the target energy station in the district cooling system is determined based on the total cooling capacity prediction value and the allocation information, specifically including: If the target operating mode is a single-station base load network mode, a multi-station base load network mode, or a dual-condition main unit air conditioning mode, then an optimization problem model is constructed based on the total cooling capacity prediction value, the corresponding candidate shutdown list, and the key parameters, and the initial value of the state array is planned based on the optimization problem model. The target value of the state array is obtained by iterative optimization based on the initial value of the state array and the key parameters corresponding to the candidate shutdown list. The target energy station to be optimally retained and operated is determined based on the target value of the state array.

5. The collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage according to claim 4, characterized in that, The step of iteratively optimizing the state array based on the initial value of the state array and the key parameters corresponding to the candidate shutdown list to obtain the target value of the state array specifically includes: Based on the initial value of the state array and the key parameters corresponding to the candidate shutdown list, traverse each candidate energy station in the candidate shutdown list, and traverse the maximum total cold storage capacity and transformer capacity of each candidate energy station; Based on all the maximum total cold storage capacity and the corresponding transformer capacity, a target value for the state data is determined, wherein the target value for the state array is the sum of the minimum transformer capacities required for the total cold storage capacity.

6. The collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage according to claim 4, characterized in that, The matching cold storage pipe section for the target energy station is specifically as follows: Based on the predicted total cooling capacity and the cold storage capacity of each pipe segment in the target energy station, task matching and pipe segment selection are performed to obtain a pairing relationship table between the energy station and the target pipe segment, and the valve opening and closing command for each cold storage loop is determined according to the pairing relationship table.

7. The collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage according to claim 3, characterized in that, If the target operating mode is a whole-station water storage cooling mode or an ice storage cooling water storage cooling mode, then according to the allocation information, all energy stations in the district cooling system are activated to store cooling in the pipeline network and ice or cooling in the water storage tank, specifically including: If the target operating mode is the whole-station water storage mode, then according to the output command corresponding to the whole-station water storage mode, start all base load hosts of all energy stations in the district cooling system to operate and all dual-condition hosts to operate in air conditioning mode, and store cold in the pipeline network and the water storage tank. If the target operating mode is ice storage and water storage mode, then according to the output command corresponding to the ice storage and water storage mode, all base load hosts of all energy stations in the district cooling system are started to operate and all dual-mode hosts are started to operate in ice-making mode to store cold in the pipeline network and store ice in the water tank.

8. A collaborative optimization system for source-side multi-energy stations and grid-side joint energy storage, characterized in that, The collaborative optimization system for source-side multi-energy stations and grid-side joint energy storage is used to implement the collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage as described in any one of claims 1-7. The collaborative optimization system for source-side multi-energy stations and grid-side joint energy storage includes: The cooling forecast and parameter determination module is used to determine the total cooling capacity forecast of the district cooling system for the next day and the configuration parameters of the district cooling system. The operation mode determination module is used to match the operation mode of the regional cooling system step by step according to the total cooling capacity prediction value and the configuration parameters, and determine the target operation mode and the corresponding allocation information. The target operation mode is one of the following: single-station base load network mode, multi-station base load network mode, dual-condition main air conditioning mode, whole-station water storage mode, and ice storage water storage mode. The energy station shutdown and pipeline selection module is used to determine the target energy station in the district cooling system based on the total cooling capacity prediction value and the allocation information if the target operation mode is a single-station base load pipeline network mode, a multi-station base load pipeline network mode or a dual-condition host air conditioning mode, and to match the cold storage pipeline section and / or water storage tank of the target energy station for cold storage. The whole-station operation module is used to start all energy stations in the regional cooling system according to the allocation information if the target operation mode is whole-station water storage mode or ice storage water storage mode, and to store ice or cold in the pipeline network and water tank.

9. A terminal, characterized in that, The terminal includes: a memory, a processor, and a collaborative optimization program for source-side multi-energy station and grid-side joint energy storage stored in the memory and executable on the processor. When the processor executes the collaborative optimization program for source-side multi-energy station and grid-side joint energy storage, it implements the steps of the collaborative optimization method for source-side multi-energy station and grid-side joint energy storage as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a collaborative optimization program for source-side multi-energy stations and grid-side joint energy storage. When the collaborative optimization program for source-side multi-energy stations and grid-side joint energy storage is executed by a processor, it implements the steps of the collaborative optimization method for source-side multi-energy stations and grid-side joint energy storage as described in any one of claims 1-7.

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