Existing building bionic flexible energy utilization transformation method combining edge collaborative crowd intelligence and phase change materials

Abstract

The invention provides an existing building bionic flexible energy utilization transformation method combining edge collaborative crowd intelligence and a phase change material, which comprises the following steps of: regulating adipogenesis and distribution by using human vegetative nerves through a bionic principle of collaboration and optimization with other systems of a body, and adopting an edge collaborative crowd intelligence technology; a flexible energy consumption target is determined by performing flexible energy consumption space analysis on an initial space in an existing building. According to a target, a flexible energy utilization strategy is formulated and implemented, and phase change material space transformation and building system control are coordinated; furthermore, the flexible energy utilization strategy is optimized, and the flexible energy utilization strategy is expanded to other transformation spaces. Flexible energy resources of all transformation spaces are combined to participate in energy demand response, virtual power plant scheduling and dynamic carbon emission factor response. Aiming at the low-carbon flexible energy consumption requirement of an existing building, a building bionic principle is used for reference, and respective prominent characteristics and advantages of various technologies such as edge collaborative crowd intelligence and phase change materials are fully combined and applied, so that the bionic flexible energy consumption transformation method is constructed.

Description

Technical Field

[0001] This invention relates to the fields of existing building renovation, bionics, and flexible energy use. Specifically, it relates to a method for bionic flexible energy use renovation of existing buildings that combines edge collaborative intelligence with phase change materials. Background Technology

[0002] like Figure 3 Existing urban buildings represent a significant area for energy conservation and carbon reduction. The older the existing building, the lower its energy efficiency standards, and the more concerning its actual energy-saving performance. Retrofitting existing buildings holds substantial potential for energy conservation and carbon reduction.

[0003] Global cities are generally shrinking. Large areas of buildings in small and medium-sized cities are vacant and abandoned. Even in large cities, although there is a siphon effect to compensate, other factors are causing vacancy rates in existing buildings to continue to rise. In the context of urban renewal, the internal functions of existing buildings are constantly changing and being remixed.

[0004] Renovating existing buildings is quite challenging. Current technologies generally require complete overhauls of the original civil engineering and electromechanical systems, which is difficult. Given the low space utilization, high vacancy rates, and increasing functional changes, the economic viability of completely renovating the civil engineering and electromechanical systems is becoming increasingly unfavorable. There is an urgent need for partial, micro-renovation, and flexible renovations. Through trial and error, iteration, and optimization, successful experiences can be accumulated and gradually promoted.

[0005] The overall installed capacity and power generation of renewable energy nationwide have reached their peak. However, the distributed renewable energy generation from existing urban buildings is still insufficient, and the local consumption rate is low. If flexible technologies do not keep pace with the continued increase in distributed power generation in the future, it will have a greater impact on the power grid, or it may come at the cost of more power curtailment.

[0006] Technologies such as virtual power plants and dynamic carbon emission factor response are emerging, but more large-scale flexible resources are needed to solve the problem of insufficient flexible regulation capacity.

[0007] In the context of flexible energy regulation, electrochemical energy storage has received widespread attention, while thermal energy storage has been neglected, resulting in relatively slow technological development. In reality, urban cooling and heating account for approximately 6-10% of total end-use energy consumption, but in summer, cooling contributes as much as 40-50% to peak urban electricity demand. This impact is becoming increasingly pronounced, especially given the climate crisis and the escalating greenhouse effect. To mitigate this peak demand, thermal energy storage, compared to electricity storage, offers advantages such as lower cost, longer lifespan, better stability, and higher security.

[0008] like Figure 3In summary, based on the above technical analysis, the current key requirements for the renovation of existing buildings are as follows: the need for flexible renovation: in the context of urban shrinkage, high vacancy rates, and flexible and changeable functions, the renovation should be able to meet the needs of partial space renovation and partial time use of existing buildings, and be easy to install, dismantle, and expand.

[0009] The need for low-carbon retrofitting: For existing buildings, it is necessary to carry out in-depth energy-saving retrofitting of conventional building envelope and electromechanical system, and also to implement new forms of retrofitting independently when conventional retrofitting is not economical.

[0010] The need for flexible transformation: On the basis of existing energy storage, we can fully develop thermal and cold storage technologies and accumulate sufficient and large-scale flexible regulation resources.

[0011] Market-driven demand: It can fully meet the needs of demand response, peak shaving and valley filling, virtual power plant dispatch response, and dynamic carbon emission factor response, and has the technical foundation for real-time linkage with the electricity market and carbon trading market.

[0012] However, existing technologies are insufficient to meet these requirements. Summary of the Invention

[0013] To address the shortcomings of the existing technologies, the purpose of this invention is to provide a biomimetic flexible energy conversion method for existing buildings that combines edge collaborative crowd intelligence with phase change materials.

[0014] This invention addresses the needs of flexible, low-carbon, and market-driven retrofitting of existing buildings. It fully combines the unique features and advantages of various technologies, such as edge collaborative intelligence and phase change materials, to construct a relatively complete biomimetic flexible energy use retrofitting method.

[0015] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0016] This invention provides a method for biomimetic flexible energy retrofitting of existing buildings that combines edge collaborative crowd intelligence with phase change materials, wherein the method includes:

[0017] Define the initial space within the existing building to be renovated;

[0018] In one implementation, the edge collaborative swarm intelligence integrates edge intelligence (EI), swarm intelligence (SI), artificial intelligence (AI), and big data. It possesses technical functions such as environmental and human activity recognition, environmental and energy consumption monitoring, building system control, load and energy consumption prediction, energy consumption strategy formulation and implementation, energy consumption strategy adaptation and optimization, and the extension and collaboration of edge intelligence to swarm intelligence.

[0019] A flexible energy consumption space analysis is performed on the initial space. In one embodiment, the flexible energy consumption space analysis includes: drawing on the biomimetic principle of human autonomic nervous system's perception of climate and space, acquiring environmental and energy consumption monitoring information of the initial space through edge collaborative swarm intelligence technology, predicting the cooling and heating load demand of the initial space for a preset time period, and initially determining the flexible energy consumption target.

[0020] In one implementation, the flexible energy use objectives include: reducing peak loads of users, flattening building energy consumption curves, increasing the absorption of renewable energy, maintaining the stability of the energy system, providing grid services, and reducing energy costs for end users, while ensuring user comfort, work efficiency, health, and convenience.

[0021] Based on the aforementioned flexible energy use analysis, a flexible energy use strategy is formulated and implemented. In one embodiment, the formulation and implementation of the flexible energy use strategy includes: drawing on the biomimetic principle of distributed control and system coordination of the human autonomic nervous system over fat and other human systems, and using edge collaborative crowd intelligence technology to formulate a flexible energy use strategy, manage the spatial transformation of phase change materials, building system control, and the coordination between the two to achieve flexible control goals, and implement the strategy.

[0022] In one embodiment, the spatial modification of phase change materials includes: drawing on the biomimetic principle of fat distribution in the human body in different climate zones, determining the phase change properties of the phase change material, the total amount, type, location, time and specific quantity to be applied in the initial space, and implementing it.

[0023] In one embodiment, the phase change material is used in various types of applications, including but not limited to: phase change energy storage devices at air conditioning terminals, stationary phase change energy storage devices, and mobile phase change energy storage devices.

[0024] In one embodiment, the phase change energy storage at the air conditioning terminal includes, but is not limited to, phase change energy storage located at the end of a fan coil unit, the end of an air conditioning box, the end of a radiant air conditioning unit, or the end of a split-type air conditioning unit.

[0025] In one embodiment, the spatially fixed phase change energy storage body includes, but is not limited to: phase change wall panels, phase change ceilings, phase change floors, phase change curtains, and phase change sunshades;

[0026] In one embodiment, the spatially active phase change energy storage body includes: in the initial space, based on the already implemented transformation of the air conditioning terminal phase change energy storage body and the spatially fixed phase change energy storage body, using edge collaborative swarm intelligence technology to link robots, temporarily configuring phase change materials according to the room layout and room activities, and controlling the delivery time, location, quantity, removal, and replacement of the phase change materials.

[0027] In one implementation, the building system control includes the control of controllable factors within the following scope: building envelope system, building energy system, and building energy system.

[0028] In one embodiment, the building envelope system includes, but is not limited to: building exterior walls, roof and insulation systems, building doors, windows, curtain walls and shading systems, building interior partition systems, and building floor systems.

[0029] In one embodiment, the building energy system includes, but is not limited to: a fresh air system, a heating and air conditioning system, a hot water system, a lighting system, an elevator system, and other equipment systems.

[0030] In one embodiment, the building energy system includes, but is not limited to: distributed renewable energy systems, battery energy storage systems, tram-building interaction V2B systems, and public power grid systems.

[0031] Based on the aforementioned flexible energy use strategy, the flexible energy use strategy is optimized. In one embodiment, the optimization of the flexible energy use strategy includes: after implementing the flexible energy use strategy within the preset time period, drawing on the biomimetic principle of the human autonomic nervous system gradually adapting and optimizing fat and other systems, and using edge collaborative swarm intelligence technology, applying Pareto solutions, when applying it to the overall renovation of different climate zones, different building types, and different spatial layouts, based on the further specific goals of the existing building renovation, selecting one or a combination of the optimal goals under the multi-objective optimization directions of optimal energy saving, optimal carbon reduction, optimal flexibility, and optimal economy, and implementing optimization.

[0032] The specific objectives of the existing building renovation mentioned above are the preferred choices made by the project leader using this invention, based on relevant interest factors such as policy guidance, market environment, business objectives, and expected benefits.

[0033] The relationship between the preliminary determination of flexible energy use targets and the optimization of flexible energy use strategies is as follows: The preliminary determination of flexible energy use targets serves as the initial basis for the formulation and implementation of flexible energy use strategies; the optimization of flexible energy use strategies, after a period of continuous operation and feedback, gradually achieves a deeper fit with the local climate zone, building type, and spatial layout. It also allows for further specific goal-oriented adjustments based on existing building renovations, choosing to continue pursuing the flexible energy use targets to achieve optimal flexibility, or adjusting the targets to achieve optimal energy saving, optimal carbon reduction, optimal economy, or overall optimality. The optimization of flexible energy use strategies involves dynamic iteration, optimization, and comprehensive correction and preparation of the renovation direction at the technical level before the expansion of flexible energy use space.

[0034] Based on the optimization of the flexible energy utilization strategy, the flexible energy utilization space is expanded. In one embodiment, the expansion of the flexible energy utilization space includes: using edge collaborative swarm intelligence technology to link robots, extending or transferring the flexible energy utilization strategy and its optimization applied in the initial space to other modified spaces, and handling the mutual superposition and linkage control of the flexible energy utilization of each space after expansion.

[0035] In one embodiment, the other modified spaces include: other adjacent modified spaces of this building, non-adjacent modified spaces, and modified spaces of other buildings.

[0036] After expanding the space for flexible energy use, implement flexible energy use and low-carbon applications. In one implementation, implementing flexible energy use and low-carbon applications includes: using edge collaborative crowdsourcing technology to connect with the Internet, uniting all flexible energy resources in the transformed space, and participating in flexible energy use market applications.

[0037] In one implementation, the flexible energy market applications include, but are not limited to: energy demand response, virtual power plant dispatch, and dynamic carbon emission factor response.

[0038] Compared with the prior art, the beneficial effects of the present invention are:

[0039] This invention addresses the needs for flexible, low-carbon, and market-driven retrofitting of existing buildings. It fully combines the distinctive features and mature advantages of various technologies, such as edge collaborative intelligence and phase change materials, to construct a relatively complete biomimetic flexible energy use retrofitting method.

[0040] like Figure 3 This invention fully utilizes the outstanding advantages of various technologies, including the following aspects:

[0041] The technological advantages of phase change materials include: the ability to store cold and heat; flexible placement and ease of installation and dismantling. Initially, they can be easily promoted, tested, and continuously optimized in limited spaces, and later scaled up. Solving the problem of "low-cost, flexible energy storage" is the "core support for energy storage" of the technological system.

[0042] The technological advantages of robots: interaction with the physical world and autonomous execution terminals. They solve the problem of "physical world data acquisition and operation execution" and serve as the "on-site execution carrier" of the technological system.

[0043] The technological advantages of edge intelligence: Spatial intelligent agents execute locally, making it easier to start and promote initially, and allowing for large-scale expansion later. It solves the problem of "real-time response and communication costs" and serves as the "local decision-making center" of the technology system.

[0044] The technological advantages of swarm intelligence include: a large-scale collaborative framework; coordination of edge intelligence; and decentralized global optimization. It solves the problem of "distributed resource collaborative optimization" and serves as the "global collaborative hub" of the technological system.

[0045] The technological advantages of artificial intelligence include autonomous decision-making and optimization algorithms, empowering edge intelligence and optimizing decision-making. Solving the problem of "autonomous decision-making in complex scenarios" is the "intelligent core" of the technology system.

[0046] The technological advantages of big data include: data processing and value mining, serving as the foundation for data processing and supporting optimized predictions. Solving the problem of "data value transformation" is the "data foundation and analysis hub" of the technological system.

[0047] The technological advantages of the Internet: It serves as a carrier for information transmission and interaction, enabling real-time data synchronization between the power trading market on both the source and load sides. It solves the problem of "real-time flow of information across entities" and acts as a "data transmission channel" for the collaboration of all technologies.

[0048] The technological advantages of biomimicry in architecture: By drawing on the human body's autonomic nervous system to regulate fat distribution, it solves the problem of "directional guidance" in the coordination between technologies, which is the "soul" that makes architecture more like an intelligent organic entity with living characteristics.

[0049] By comprehensively utilizing the above technologies, this invention achieves the following objectives:

[0050] It meets the needs of flexible renovation of existing buildings: in the case of urban shrinkage, high vacancy rate and flexible and changeable functions, it can meet the needs of partial space renovation and partial time use of existing buildings, and can be easily installed, dismantled and expanded.

[0051] It meets the needs of low-carbon retrofitting of existing buildings: for existing buildings, it can be carried out in conjunction with conventional building envelope and electromechanical system energy-saving retrofitting, and can also be carried out independently in cases where conventional retrofitting is not economical.

[0052] It meets the needs of flexible retrofitting of existing buildings: it can fully develop thermal and cold storage technologies on the basis of existing energy storage, and accumulate sufficient and large-scale flexible regulation resources.

[0053] It meets the needs of the existing building market: it can fully meet the needs of demand response, peak shaving and valley filling, virtual power plant dispatch response, and dynamic carbon emission factor response, and has the technical foundation for real-time linkage with the electricity market and carbon trading market. Attached Figure Description

[0054] Figure 1 This is a flowchart illustrating the biomimetic flexible energy conversion method for buildings in this invention.

[0055] Figure 2This is a schematic diagram showing the application types of phase change materials and the hierarchical relationship between various flexible resources in a building structure in this invention.

[0056] Figure 3 This is a schematic diagram illustrating the relationship between the background technology (including current problems and improvement needs) and the outstanding advantages of various technologies in this invention.

[0057] Figure 4 This is a schematic diagram illustrating the existing architectural biomimetic principle of combining edge collaborative crowd intelligence with phase change materials in this invention. The diagram uses biological organisms as the counterpart for architectural biomimetic, while the text uses the human body as an example of a biological organism.

[0058] Figure 5 This is a schematic diagram illustrating the process of optimizing flexible energy use strategies. Detailed Implementation

[0059] To enhance understanding of the present invention, the technical methods and embodiments will be further described in detail below with reference to the accompanying drawings. This part is only used to explain the present invention and does not constitute a limitation on the scope of protection of the present invention.

[0060] like Figure 1 As shown, the method includes the following steps:

[0061] Step A100: Define the initial space within the existing building to be renovated; specifically, in this embodiment, the initial space is the initially selected renovation area within the existing building, possessing complete and clear boundaries, as well as typicality and representativeness. For example, a specific room, several rooms, a specific floor, or several floors within an office building.

[0062] Step A200 employs edge collaborative swarm intelligence technology. This edge collaborative swarm intelligence integrates edge intelligence (EI), swarm intelligence (SI), artificial intelligence (AI), and big data. It possesses technical functions such as environmental and human activity recognition, environmental and energy consumption monitoring, building system control, load and energy consumption prediction, energy use strategy formulation and implementation, energy use strategy adaptation and optimization, and the extension and collaboration of edge intelligence to swarm intelligence. Specifically, in this embodiment, the edge collaborative swarm intelligence technology coordinates the entire process of flexible energy use space analysis (A300), flexible energy use strategy formulation and implementation (A400), flexible energy use strategy optimization (A500), flexible energy use space expansion (A600), and flexible energy use low-carbon application (A700).

[0063] Step A300: Perform flexible energy consumption space analysis on the initial space. In one implementation, the flexible energy consumption space analysis includes: drawing on the biomimetic principle of human autonomic nervous system's perception of climate and space, acquiring environmental and energy consumption monitoring information of the initial space through edge collaborative swarm intelligence technology, predicting the cooling and heating load demand of the initial space for a preset time period, and initially determining the flexible energy consumption target.

[0064] Specifically, such as Figure 4 In this embodiment, the biomimetic principle of human autonomic nervous system's perception of climate and space is borrowed from the B110 model. Architectural biomimicry can be applied to information perception and processing, from capturing biological signals to analyzing architectural data. When the human autonomic nervous system regulates fat distribution, it first uses "biosensing units" such as skin temperature receptors and visceral chemical sensors to accurately capture signals of climate and environmental changes, such as sensing low temperatures in cold weather and environmental heat in warm weather. These signals are integrated and analyzed by the hypothalamus's "central processing module," distinguishing the impact of the environment on body temperature, and thus triggering fat regulation commands to determine the direction of fat decomposition or storage. The building edge collaborative swarm intelligence technology borrows this mechanism, deploying multimodal sensors such as temperature, sunlight, and humidity as "building sensing nodes" at the edge of the initial space to be renovated within an existing building, collecting real-time outdoor climate and indoor thermal environment data. Edge computing nodes act as "building hubs," performing preprocessing such as noise reduction and filtering on the collected raw data. After removing invalid information, the data is input into the heat demand prediction model to accurately determine the heat storage and release requirements of phase change materials in different regions. For example, high-temperature regions need to increase the heat storage of phase change materials, while low-temperature regions need to activate the heat release of phase change materials. This realizes the transformation from "passively receiving data" to "actively predicting demand," improving the accuracy of phase change material distribution control.

[0065] In one implementation, the flexible energy use objectives include: not reducing user comfort, work efficiency, health and convenience, reducing user peak load, flattening building energy consumption curves, increasing the absorption of renewable energy, maintaining the stability of the energy system, providing grid services, and reducing end-user energy costs.

[0066] like Figure 1 In step A400, based on the aforementioned flexible energy use analysis, a flexible energy use strategy is formulated and implemented. In one implementation, the formulation and implementation of the flexible energy use strategy includes: drawing on the biomimetic principle of distributed control and system collaboration of the human autonomic nervous system over fat and other human systems, and using edge collaborative swarm intelligence technology to formulate a flexible energy use strategy, manage the spatial modification of phase change materials, building system control, and the collaboration between the two to achieve flexible control goals, and implement the strategy.

[0067] Specifically, such as Figure 4In embodiments B121 and B122, this example draws on the biomimetic principles of distributed control and system coordination of the human autonomic nervous system over fat and other human systems. Architectural biomimicry can be applied in two ways: in terms of distributed control, from nerve ending regulation to unit node management; and in terms of system coordination, from nerve antagonistic balance to multi-system linkage. Firstly, regarding distributed control, the human autonomic nervous system lacks a centralized control center. The sympathetic and parasympathetic nerve endings are distributed throughout the body's adipose tissue, forming a distributed regulatory network. In cold weather, sympathetic nerve endings act synchronously in the body's adipose areas, promoting the accumulation of visceral and subcutaneous fat; in warm weather, parasympathetic nerve endings dominate, ensuring even distribution of subcutaneous fat. Each ending responds independently yet coordinates with others, avoiding the delay problem of a single control center. The building edge collaborative swarm intelligence technology divides the initial space to be renovated within an existing building into one or more independent spatial units. Each unit embeds intelligent computing nodes, constructing a distributed control network. Each node independently monitors changes in the thermal environment of its unit, autonomously adjusting the amount and activation state of the phase change material (PCM) within the unit. For example, if the temperature rises in an office unit, the node can autonomously increase the amount of PCM in that area; if the temperature drops in a meeting room unit, the node can activate the PCM to release heat. Nodes synchronize their states through information exchange, avoiding signal delays and energy waste from central control and improving the response speed of PCM distribution adjustment. Next, regarding system coordination, the autonomic nervous system regulates fat distribution not in isolation, but in a collaborative network with the circulatory and metabolic systems. In cold weather, the sympathetic nervous system not only promotes fat breakdown for energy but also simultaneously drives the circulatory system to accelerate blood flow, transporting fat breakdown products throughout the body. In warm weather, the parasympathetic nervous system, while inhibiting fat breakdown and promoting its even distribution, coordinates the metabolic system to reduce energy consumption. Both maintain fat balance through antagonism and cooperate with other systems to ensure stable body temperature and adequate energy supply and demand, forming a multi-system coordinated steady-state regulatory mechanism, rather than a single fat regulation mechanism. Building-edge collaborative crowdsourcing technology draws on this collaborative logic to coordinate the initial spatial transformation of phase change materials with various modules such as the building envelope, building energy systems, and building power systems. When the outside temperature rises, much like the human sympathetic nervous system, the phase change materials are activated to store heat, reducing heat transfer into the interior. Simultaneously, the building envelope enhances insulation performance and inhibits excessive activation of energy systems (such as air conditioning). When the temperature drops, similar to the parasympathetic nervous system, the phase change materials are activated to release heat, replenishing the indoor temperature and reducing energy consumption of energy systems (such as heating systems). In all situations, it can be integrated with building energy systems, such as photovoltaics, battery storage, and V2B systems, to allocate power supply and consumption patterns, increase local renewable energy absorption, enhance the building's flexible power consumption capacity, and reduce rigid demand on the municipal power grid. Each module both mutually constrains and prevents overload of a single system while cooperating to ensure a stable indoor environment, adapting to external climate changes and achieving a balance between energy conservation and comfort.

[0068] like Figure 1 In step A410, in one implementation, the spatial modification of the phase change material includes: drawing on the biomimetic principle of fat distribution in the human body in different climate zones, determining the phase change properties of the phase change material, the total amount, type, location, time and specific quantity to be applied in the initial space, and implementing it.

[0069] Specifically, such as Figure 4 In this embodiment, B210 draws inspiration from the biomimetic principle of fat distribution in the human body across different climate zones. Architectural biomimicry could be based on the idea that human fat is a natural energy-storing and temperature-regulating material, absorbing or releasing heat through a solid-liquid phase change at a melting point of around 30°C to maintain stable body temperature. Fat distribution varies across different climate zones: in cold regions, there is more fat around the internal organs, which helps keep them warm and reduces heat loss; thicker subcutaneous fat provides continuous energy for warmth. In hot regions, there is less subcutaneous fat, which is more evenly distributed, aiding in heat dissipation; relatively more fat is found in the limbs, contributing to localized temperature control and overall heat dissipation. From an architectural biomimicry perspective, buildings need to adapt to environmental temperature regulation, and the energy-storing and temperature-regulating mechanism of human fat can provide a useful reference. The reason for this reference is that both require responses to external temperature changes, achieving internal thermal environment stability through material properties. Specifically, for buildings in cold regions, mimicking the abundance of fat around the internal organs, materials with suitable phase change temperatures should be prioritized in the critical "internal organ" spaces—spaces requiring high temperature stability. Drawing inspiration from the characteristic of thick subcutaneous fat, the amount of phase change material used on the exterior walls and the inner surface of the roof is also increased accordingly to enhance thermal insulation and heat storage capacity. For buildings in hot regions, mimicking the characteristic of less and more uniform subcutaneous fat, the amount of phase change material used on the exterior walls and the inner surface of the roof is reduced. Instead, phase change material is used evenly in the surrounding areas of the building's "limbs," such as the buffer space on the outer side of the building, to assist in temperature control and heat dissipation, thereby improving the building's adaptability.

[0070] In one implementation, the phase change material is used in various types of applications, including but not limited to: phase change energy storage at the air conditioning terminal, stationary phase change energy storage in space, and mobile phase change energy storage in space.

[0071] In one implementation, the phase change energy storage device at the air conditioning terminal includes, but is not limited to, phase change energy storage devices located at the end of fan coil units, air conditioning boxes, radiant air conditioning terminals, and split-type air conditioning terminals.

[0072] Specifically, the selection of phase change energy storage (PCE) materials for air conditioning terminals needs to match the existing terminal's cooling temperature and indoor demand to ensure efficient cold storage / release. PCE materials with a phase change temperature of 20-24℃, such as paraffin wax or fatty acids, are chosen, close to the comfortable indoor temperature of 24-26℃, to avoid condensation due to excessively low temperatures during cold release. This also ensures compatibility with the air conditioning terminal's cooling temperature. For example, a fan coil unit outlet temperature of 7-12℃ is sufficient for cold storage. The packaging method should be selected based on the terminal type to ensure safety and efficiency: fan coil units / air conditioning units can be packaged in aluminum or stainless steel plates with good thermal conductivity, or in flexible, easy-to-install high-density polyethylene (HDPE) bags. Radiant terminals can use gypsum composite boards, compatible with building materials; or thin metal honeycomb panels, offering lightweight advantages. Split air conditioners can use flexible silicone bags, which are bendable and easily conform to the curved surface of the indoor unit. PCE materials with a phase change heat of ≥180kJ / kg are preferred to ensure sufficient cold storage capacity per unit volume and reduce material space requirements. The key steps in retrofitting air conditioning terminal units with phase change energy storage systems are as follows: First, the performance of the existing terminals needs to be assessed. This involves testing cooling parameters such as chilled water flow rate, inlet and outlet water temperature, and air volume of fan coil units to determine the potential for cold storage. Simultaneously, the installation space, including the return air height and air conditioning unit dimensions, needs to be measured to ensure component compatibility. Next, phase change components are designed and customized based on the terminal type and space dimensions, clearly defining component size and layout (avoiding motors and water pipe interfaces to avoid obstructing core components such as the evaporator and fan impeller). A 3-5cm thick insulation material is then wrapped around the components to reduce cold loss. Finally, the components are installed using non-destructive methods such as clips, brackets, and Velcro. Compatibility testing and monitoring of the air conditioning system are then conducted. The system's cooling rate during operation (requiring full cooling within 2-3 hours) and the indoor temperature maintenance time after system shutdown (target 2-4 hours) are considered. The amount of phase change material or the arrangement of components are adjusted as needed. If the component surface temperature is lower than the indoor dew point, a breathable anti-condensation layer is added or local exhaust ventilation is increased for dehumidification. Finally, the control logic is optimized using edge collaborative crowd intelligence technology. There is no need to modify the original air conditioning control system. Only temperature sensors are added near the components. When the component temperature drops below 20°C (cooling is complete), the terminal load is reduced through the original air conditioning controller (e.g., by reducing the fan speed). After shutdown, if the indoor temperature rises above 26°C, the terminal fan is turned on to run at low speed to accelerate the release of cooling from the phase change material.

[0073] In one implementation, the spatially fixed phase change energy storage body includes, but is not limited to: phase change curtains, phase change sunshades, phase change ceilings, phase change floors, and phase change wall panels;

[0074] In one implementation, the spatially active phase change energy storage body includes: in the initial space, based on the already implemented transformation of the air conditioning terminal phase change energy storage body and the spatially fixed phase change energy storage body, using edge collaborative swarm intelligence technology to link robots, temporarily configuring phase change materials according to the room layout and room activities, and controlling the delivery time, location, quantity, removal, and replacement of the phase change materials.

[0075] Specifically, in the formulation and implementation of flexible energy use strategies for buildings, the transformation of three types of phase change energy storage bodies forms a collaborative system of "basic guarantee - fixed support - dynamic adjustment" through functional complementarity and scenario adaptation. Phase change energy storage bodies at the air conditioning terminal are the "basic response units" for energy use regulation, directly related to the air conditioning system load. Relying on air conditioning terminal equipment, they provide underlying support for flexible energy use, ensuring the stable operation of core energy-consuming equipment and reducing energy consumption costs, serving as a key link between buildings and energy systems. Fixed phase change energy storage bodies in space (wall panels, ceilings, etc.) constitute a "static support network" for energy use regulation, embedded in the building envelope. Through their own phase change characteristics, they buffer indoor temperature fluctuations, reducing the frequency of air conditioning start-ups and shutdowns. This extends the effective lifespan of air conditioning terminal energy storage bodies and creates a stable indoor thermal environment, serving as the basic carrier for achieving passive energy saving and flexible energy use in buildings. Active phase change energy storage bodies in space are the "dynamic adjustment supplement" for energy use optimization. Relying on edge intelligence and robots, phase change materials can be flexibly added or removed according to room layout (such as temporary expansion of meeting rooms) and activity needs (such as short-term high-traffic gatherings). When fixed energy storage coverage is insufficient or energy demand changes abruptly, precise replenishment of distribution locations and quantities can achieve "on-demand energy allocation," shifting flexible energy use from a fixed mode to dynamic adaptation and further improving energy flexibility and efficiency. The combination of these three elements enables full-scenario coverage of building energy use, from basic guarantees to dynamic optimization.

[0076] Specifically, the modification of the air conditioning terminal phase change energy storage body and the space fixed phase change energy storage body is relatively complex, but the number of modifications is low and the frequency is low, so it can be done manually; while the space mobile phase change energy storage body has a simple modification procedure, but the number of modifications is high and the frequency is high, so it can be implemented by edge system swarm intelligence linkage robot.

[0077] like Figure 1 In step A420, in one implementation, the building system control includes the control of controllable factors within the following scope: building envelope system, building energy system, and building energy system.

[0078] In one implementation, the building envelope system includes, but is not limited to: building exterior walls, roof and insulation systems, building doors, windows, curtain walls and shading systems, building interior partition systems, and building floor systems.

[0079] In one implementation, the building energy system includes, but is not limited to: a fresh air system, a heating and air conditioning system, a hot water system, a lighting system, an elevator system, and other equipment systems.

[0080] In one implementation, the building energy system includes, but is not limited to: distributed renewable energy systems, battery energy storage systems, tram-building interaction V2B systems, and public power grid systems.

[0081] Specifically, such as Figure 2 By utilizing both fixed and mobile phase-change energy storage systems in space, combined with the thermal inertia of the building's main structure, the energy storage of the building envelope system can be improved. Furthermore, by using phase-change energy storage systems at the air conditioning terminals, air conditioning systems can be transformed into flexible phase-change air conditioners, and combined with other flexible energy systems such as lighting and hot water, the energy storage of the building's energy consumption system can be improved. Simultaneously, edge-collaborative crowdsourcing technology, based on the coordinated energy storage of the building envelope system and the building's energy consumption system, integrates energy storage from other building energy systems, such as battery energy storage systems, energy storage functions in V2B systems involving trams and buildings, and other forms of energy storage, to jointly explore the flexible resources of existing buildings, laying the foundation for participation in energy demand response, virtual power plant scheduling, and dynamic carbon emission factor response.

[0082] like Figure 1 In step A500, the flexible energy use strategy is optimized according to the aforementioned implementation strategy. In one embodiment, the optimization of the flexible energy use strategy includes: after implementing the flexible energy use strategy within the preset time period, drawing on the biomimetic principle of the human autonomic nervous system gradually adapting and optimizing fat and other systems, and using edge collaborative swarm intelligence technology, applying Pareto solutions, when applying it to the overall renovation of different climate zones, different building types, and different spatial layouts, based on the specific goals of the existing building renovation, selecting one or a combination of the optimal goals under the multi-objective optimization directions of optimal energy saving, optimal carbon reduction, optimal flexibility, and optimal economy, and implementing the optimization.

[0083] Specifically, such as Figure 4In this embodiment, the B130 building borrows the biomimetic principle of how the human autonomic nervous system gradually adapts and optimizes fat and other systems. Building biomimetic can be seen in its adaptation and optimization, progressing from long-term adaptation to dynamic iterative upgrades. The mechanism by which the human autonomic nervous system regulates fat distribution is continuously optimized through long-term natural adaptation. In cold regions, people gradually adjust their fat distribution strategy due to long-term adaptation to the cold environment, resulting in thicker visceral fat for enhanced insulation; in hot regions, people develop a pattern of evenly distributed subcutaneous fat to reduce heat accumulation, achieving long-term adaptation of fat distribution to climate. The building edge collaborative swarm intelligence technology borrows from the long-term adaptation process of the human body. During dynamic operation and maintenance, it continuously adapts and optimizes energy consumption strategies through fault diagnosis and troubleshooting, data cleaning, and dual-drive optimization of AI data and actual operating data. For example... Figure 5 During operation and maintenance, energy strategies gradually become more deeply aligned with specific climate zones, building types, and spatial layouts. Based on the specific goals of existing building renovations, optimization is achieved through a multi-objective approach encompassing energy conservation, carbon reduction, flexibility, and economic efficiency. This involves selecting one or a combination of these optimal goals to achieve optimization and dynamic iterative upgrades. Specifically, energy conservation aims to minimize the building's energy consumption during operation; carbon reduction aims to minimize carbon emissions during operation or throughout its entire lifecycle; flexibility aims to maximize the utilization rate of local renewable energy; economic efficiency aims to minimize the dynamic investment payback period or internal rate of return for technological measures; and comprehensive optimization involves selecting multiple factors, with the choice based on the achievement of the overall objective. Simultaneously, operation and maintenance data for individual projects are uploaded to a central database, continuously driving the establishment of a multi-dimensional operation and maintenance database. This database covers temperature and humidity fluctuations in different climate zones, differences in heat demand among various building types (residential / public / industrial), heat distribution characteristics of building interior spatial layouts (e.g., large-span factories / small-unit residences), and the implementation status of different projects in terms of goal setting and strategy optimization across multiple objectives such as energy conservation, carbon reduction, flexibility, and economic efficiency. This further enhances the horizontal comparison function for optimizing the operation and maintenance of individual projects.

[0084] like Figure 1 In step A600, the flexible energy utilization space is expanded according to the optimized flexible energy utilization strategy. This expansion includes: using edge collaborative swarm intelligence technology to link robots, extending or transferring the flexible energy utilization strategy and its optimization applied in the initial space to other modified spaces, and handling the superimposed effects and coordinated control of the flexible energy utilization in each expanded space.

[0085] The other modified spaces mentioned include: other adjacent modified spaces of this building, non-adjacent modified spaces, all other spaces of this building, and modified spaces of other buildings.

[0086] like Figure 1In step A700, after expanding the flexible energy use space, flexible energy use and low-carbon applications are implemented. This implementation includes: leveraging edge collaborative crowdsourcing technology, connecting with the internet, and uniting all flexible energy resources in the transformed space to participate in flexible energy use market applications.

[0087] In one implementation, the flexible energy market application includes, but is not limited to: energy demand response, virtual power plant dispatch, and dynamic carbon emission factor response.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them; although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications can still be made to the specific implementation of the present invention or equivalent substitutions can be made to some technical features without departing from the spirit of the technical solutions of the present invention, and all such modifications and substitutions should be covered within the scope of the technical solutions claimed in the present invention.

Claims

1. A method for biomimetic flexible energy retrofitting of existing buildings that combines edge collaborative crowd intelligence with phase change materials, characterized in that, The method includes: Define the initial space within the existing building to be renovated; The aforementioned edge-collaborative swarm intelligence integrates edge intelligence (EI), swarm intelligence (SI), artificial intelligence (AI), and big data. It possesses technical functions such as environmental and human activity recognition, environmental and energy consumption monitoring, building system control, load and energy consumption prediction, energy consumption strategy formulation and implementation, energy consumption strategy adaptation and optimization, and the technical capabilities for extending and collaborating edge intelligence to swarm intelligence. A flexible energy consumption space analysis is performed on the initial space. This analysis includes: drawing on the biomimetic principle of human autonomic nervous system's perception of climate and space, and using edge collaborative swarm intelligence technology to acquire environmental and energy consumption monitoring information of the initial space, predicting the cooling and heating load demand of the initial space over a preset time period, and initially determining flexible energy consumption targets; Based on the aforementioned flexible energy use analysis, a flexible energy use strategy is formulated and implemented. This strategy includes: drawing inspiration from the biomimetic principles of distributed control and system collaboration of the human autonomic nervous system over fat and other human systems; utilizing edge collaborative crowd intelligence technology to formulate a flexible energy use strategy; managing the spatial modification of phase change materials, building system control, and the collaboration between the two to achieve the aforementioned flexible energy use goals; and implementing the strategy. The aforementioned spatial modification of phase change materials includes: drawing on the biomimetic principle of fat distribution in the human body in different climate zones, determining the phase change properties of the phase change materials, the total amount, type, location, time and specific quantity to be applied in the initial space; The application types of the phase change materials include: phase change energy storage in air conditioning terminals, stationary phase change energy storage in space, and mobile phase change energy storage in space; The building system control includes the control of controllable factors within the following scope: building envelope system, building energy system, and building energy system; After formulating and implementing a flexible energy use strategy, the strategy is optimized. This optimization includes: after implementing the flexible energy use strategy within the preset time period, drawing inspiration from the biomimetic principle of how the human autonomic nervous system gradually adapts and optimizes fat and other systems, using edge collaborative crowd intelligence technology and applying Pareto solutions, when applying it to overall renovations in different climate zones, building types, and spatial layouts, based on the specific goals of the existing building renovation, selecting one or a combination of the following multi-objective optimization directions—optimal energy saving, optimal carbon reduction, optimal flexibility, and optimal economy—and implementing optimization. Based on the optimization of the flexible energy utilization strategy, the flexible energy utilization space is expanded. The expansion of the flexible energy utilization space includes: using edge collaborative swarm intelligence technology to link robots, expanding or transferring the flexible energy utilization strategy and its optimization applied in the initial space to other modified spaces, and handling the mutual superposition and linkage control of the flexible energy utilization of each space after expansion; Other remodeled spaces include: other adjacent remodeled spaces of this building, non-adjacent remodeled spaces, and remodeled spaces of other buildings; After expanding the space for flexible energy use, participate in flexible energy use and low-carbon applications. This participation includes: leveraging edge-collaborative crowdsourcing technology, connecting with the internet, and uniting all flexible energy resources in the transformed space to participate in energy demand response, virtual power plant scheduling, and dynamic carbon emission factor response.

2. The method for biomimetic flexible energy retrofitting of existing buildings combining edge collaborative crowd intelligence and phase change materials as described in claim 1, characterized in that, The aforementioned flexible energy use objectives include: reducing peak loads, flattening building energy consumption curves, increasing the absorption of renewable energy, maintaining the stability of the energy system, providing grid services, and reducing end-user energy costs, all while ensuring user comfort, work efficiency, health, and convenience.

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