Energy Optimization and Heat Recovery System

Abstract

The invention relates to an energy optimization and heat recovery system used in data centers for energy management and cooling systems. Specifically, it enables efficient and sustainable data center operation by achieving dynamic energy optimization, cooling management, and waste heat recovery using artificial intelligence-powered algorithms.

Description

1 TARIFF Energy Optimization and Heat Recovery System TECHNICAL AREA 5 The invention is used in the field of energy management and cooling systems in data centers, in particular. Dynamic energy optimization and cooling management using AI-powered algorithms. and achieve efficient and sustainable data center operation by recovering waste heat. It is related to energy optimization and heat recovery systems that enable this. 10 PREVIOUS TECHNIQUE Today, the rapidly increasing energy needs of data centers bring with them a number of technical and environmental challenges. This also brings problems. In particular, the recycling of the large amounts of heat generated in these centers is 15. The inability to use it via this route stands out as a significant drawback. High energy consumption and The large amount of heat generated makes it difficult for data centers to operate efficiently; this situation Traditional cooling systems lead to both energy waste and environmental impacts. These methods increase operating costs by consuming more energy than necessary, and the resulting Excess heat harms the environment and leads to an increase in the carbon footprint. Therefore, 20 Significant technical issues regarding the sustainability and efficiency of existing systems. It is located. As a result of research conducted in the literature, the application numbered “2024 / 017754” and “WASTE HEAT RECOVERY” A Turkish patent application titled "ACQUISITION SYSTEM" has been found. The aforementioned 25 The application is for an industrial open and closed display type unit containing at least one compressor. refrigerators / freezers, household refrigerators, industrial storage systems refrigerators / freezers, heat pumps and devices and applications that undergo defrosting Waste heat sources from condensers, compressors and fans used in these fields Defrosting is performed to prevent frost and ice buildup in the evaporator. 30 removing the condensation water formed during the process by evaporation from the system. It relates to the waste heat recovery system that provides this. However, the data in the mentioned application... used in energy management and cooling systems in centers, especially artificial intelligence. Dynamic energy optimization, cooling management, and waste management using supported algorithms. By enabling heat recovery, efficient and sustainable data center operation is achieved. 35 an indication of an energy optimization and heat recovery system that enables this None have been encountered. 2 Ultimately, the problems mentioned above, which cannot be solved with current technology, are the subject of this technical analysis. This has made it necessary to make an innovation in the field. A BRIEF DESCRIPTION OF THE INVENTION The present invention aims to eliminate the aforementioned disadvantages and introduce new technologies to the relevant technical field. It is related to energy optimization and heat recovery systems in order to bring advantages. The main purpose of the invention is to improve energy management and cooling systems in data centers. dynamic energy 10 used, especially by using artificial intelligence-powered algorithms by optimizing, managing cooling and recovering waste heat, it is efficient and The goal is to ensure sustainable data center operation. All the purposes mentioned above and those that will emerge from the detailed explanation below. The present invention aims to achieve energy management and cooling in data centers. 15 dynamic systems used in the field, especially using artificial intelligence-powered algorithms. By enabling energy optimization, cooling management and waste heat recovery, it is efficient and Energy optimization and heat recovery that enable sustainable data center operation. It is a data acquisition system, characterized by having sensors and IoT devices; the aforementioned sensors and IoT devices collect data such as temperature, server load and energy consumption within the data center. Intelligent cooling and airflow prevents unnecessary operation of the cooling system by collecting air. The unit collects excess heat from the intelligent cooling and airflow unit, converting that heat into heat. heat recovery that transfers heat to the thermal storage system via heat exchangers or heat transfer elements The recovery module communicates with the intelligent cooling and airflow unit and is AI-powered. The temperature it receives from the intelligent cooling and airflow unit via the software running inside is 25. Management unit that analyzes server load and energy consumption data in real time. It includes. The advantages of the current invention, along with its structure and additional elements, can be best utilized in 30 years. For it to be understood, it must be considered together with the figures explained below. BRIEF DESCRIPTION OF THE FIGURES Figure 1 shows a representative image of the energy optimization and heat recovery system that is the subject of the invention. It is a representation. 3 The drawings do not necessarily need to be scaled and are necessary for understanding the invention. Details that are not present may have been overlooked. Furthermore, at least to a large extent... Elements that are identical or at least have substantially identical functions are numbered the same. It is shown. 5 REFERENCE NUMBERS 1. Administrative unit 2. Smart cooling and airflow unit 10 3. Heat recovery module 4. Real-time monitoring and automation module DETAILED DESCRIPTION OF THE INVENTION This detailed explanation describes the energy optimization and heat recovery system that is the subject of the invention. it will not create any limiting effect on a better understanding of the subject. This is explained with examples. Energy optimization and heat recovery system, management unit (1), smart cooling and air 20 flow unit (2), heat recovery module (3), real-time monitoring and automation module (4) It includes the management unit (1), which communicates with the intelligent cooling and airflow unit (2), artificial Intelligent cooling and airflow via software running within it. It receives temperature, server load and energy consumption data from the unit (2) in real time It is the unit that analyzes as follows: Smart cooling and airflow unit (2), sensors and IoT 25 Equipped with these devices, the aforementioned sensors monitor temperature and server load within the data center. and by collecting data such as energy consumption, it prevents the cooling system from running unnecessarily. It is a unit. The heat recovery module (3) collects the excess heat obtained from cooling systems, heat is transferred to a thermal storage system via heat exchangers or heat transfer elements. It is the module that transmits. Real-time monitoring and automation module (4), data center energy 30 Visualizes consumption, heat distribution, and optimization status, and allows intervention when necessary. It is a module that provides the operator with data about the system in order to enable them to make informed decisions. The energy optimization and heat recovery system aims to improve data center energy efficiency and It works by relying on certain elements to recover excess heat. The system uses artificial intelligence, 35 Sensors establish a dynamic balance between heat recovery components, ensuring optimum efficiency. It provides energy optimization and heat recovery systems to achieve energy efficiency. 4 This ensures an efficient cooling method by preventing unnecessary energy consumption. Cost savings are achieved through heat recovery and intelligent cooling management for the business. Costs are decreasing. Environmental sustainability is achieved and the carbon footprint is reduced. By reducing costs, the data center is made more environmentally friendly. System scalability Thanks to this, it can be easily integrated into small, medium, and large-scale data centers. 5 With energy optimization and heat recovery systems;  Analyzes server loads and energy consumption in real time. Learning using algorithms to analyze the data center's past energy consumption and external weather conditions. It provides preventive optimization according to the plan. 10  Sensors and IoT devices prevent unnecessary operation of the cooling system. Air It determines the most efficient cooling paths using flow direction systems.  Excess heat obtained from cooling systems is transferred to thermal conductivity via heat exchangers. The heat is transferred to the storage system. This heat is used in the hot water system of the building where the data center is located. It is evaluated by directing it to the system or the heating system of surrounding buildings. 15  Data center's energy consumption, heat dissipation, and optimization status It visualizes the system's operation in real time through administrative panels. They can view and intervene in these images. Smart cooling with sensors in the energy optimization and heat recovery system and 20 air flow unit (2) temperature, server load and energy consumption inside the data center collects data. The AI-powered management unit (1) analyzes this data and cools It optimizes the systems. Cooling systems can be free cooling or mechanical cooling. It makes the most efficient choice among the options. The excess heat generated during the cooling process is recovered. It is collected by the gain module (3) and directed to the building's heating system. Real-time 25 Monitoring and automation module (4) provides the operator with data about the system and when needed It allows for intervention.

Claims

REQUESTS 1. Used in the field of energy management and cooling systems in data centers, especially 5 Dynamic energy optimization and cooling using AI-powered algorithms. by managing and recovering waste heat, an efficient and sustainable data system. Energy optimization and heat recovery that enable centralized operation. It is a system, and its feature is;  having sensors and IoT devices, 10 with the aforementioned sensors and IoT devices data such as temperature, server load, and energy consumption within the data center Smart cooling that prevents unnecessary operation of the cooling system by collecting data. air flow unit (2),  Collecting the excess heat obtained from the intelligent cooling and airflow unit (2), heat Thermal storage via heat exchangers or heat transfer elements 15 heat recovery module (3) that transfers heat to the system,  AI-powered, communicating with the smart cooling and airflow unit (2), Intelligent cooling and airflow through software running inside. It receives temperature, server load and energy consumption data from the unit (2) in real time. Management unit that analyzes in time (1) 20 It includes.

2. An energy optimization and heat recovery system in accordance with Claim 1, whose characteristic is; data visualizes the energy consumption, heat distribution, and optimization status of the center. Data about the system is provided to the operator to allow for intervention when necessary. 25 It includes a real-time monitoring and automation module (4) that provides.

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