商业大楼用HVAC最佳化能源管理软体的全球市场 - 市场规模，竞争情形(2024年～2029年)

范例视图

全球商业建筑 HVAC 优化能源管理软体市场规模预计将从 2023 年 36.5 亿美元的基准值成长到 2029 年达到 58.3 亿美元。

相对于其占地面积，资料中心占市场收入的很大一部分，占 2024 年 HVAC 优化软体总收入的 11.4%（4.49 亿美元）。 HVAC 冷却可占资料中心总能源消耗的 40%，因此高效的 HVAC 管理至关重要。资料中心中人工智慧驱动的 HVAC 解决方案可根据伺服器负载等级、外部气候条件和内部温度等即时资料动态调整冷却输出。

由于技术进步、监管压力以及对能源效率需求的认识不断提高，商业建筑 HVAC 优化的能源管理软体市场预计在未来五年内将显着增长。

本报告研究和分析了商业建筑暖通空调优化市场的全球能源管理软体，提供了市场规模、趋势和推动因素、挑战和障​​碍以及竞争格局等资讯。我们也仔细研究了人工智慧驱动的能源管理技术如何改变暖通空调系统的运作方式，提高运作效率和永续性。

样品view

能源管理软体公司特色范例

目录

序文

调查范围

调查手法

定义

第1章 简介

第2章 核心技术

• 感测器、连网设备、物联网
• 分析、人工智慧、机器学习
• 边缘/云端运算
• 使用人工智慧的 HVAC 优化技术堆迭

第3章 商业大楼的能源管理的现状

• 商业建筑能源消耗概览
• 商业建筑的能源使用模式
• 商业建筑的二氧化碳排放量
• 技术采用率
• HVAC 能源管理解决方案成熟度模型

第4章 主要使用案例与用途

• 提高能源绩效
• 减少二氧化碳排放
• 预测性维护与故障侦测
• 基于占用情况的 HVAC 控制
• 根据季节和天气进行最佳化
• 室内空气品质 (IAQ) 和 HVAC 优化

第5章 垂直市场用途和机会

• 垂直市场概要
• 办公室
• 零售
• 饭店·食品服务
• 仓库
• 资料中心

第6章 市场趋势与促进因素

• 世界能源情势
• 再生能源、能源转型
• 建筑与电网整合
• 监管与政策环境
• 经济因素与房地产趋势
• 工作场所动态的变化
• 都市化与智慧城市举措
• 永续发展、ESG、绿色金融
• 认证和行业标准

第7章 课题与阻碍

• 财务障碍
• 与旧系统集成
• 技能与劳动力障碍
• 资料隐私和安全
• 改造及危险房

第8章 全球市场的预测(2024年～2029年)

• 全球市场的预测
• 市场明细:各业界

第9章 地区市场明细与分析

• 市场明细:各地区
• 地区特有的市场促进因素与阻碍

第10章 活用了AI的HVAC软体的竞争情形

• 企业的地区分布
• 企业的分布:各规模
• 企业的分布:各年数

第11章 主要企业的策略性定位

• 大楼自动化企业
• HVAC的专家
• 创新的Start-Ups和新兴企业

第12章 投资趋势与M&A

• 合併和收购
• 伙伴关係和合作
• 投资概要
• 地理投资趋势
• 值得注意的投资交易

This report is a new 2024 study that provides a detailed market forecast to 2029, broken down by region and vertical market.

In today's complex commercial real estate landscape, energy management has become a critical focus for property and facilities managers. Optimizing energy use is not just about lowering costs, it has become a key factor in achieving sustainability and resource efficiency.

This new research takes an in-depth look at how artificial intelligence-driven energy management technologies will transform the way HVAC systems operate, enhancing both operational efficiency and sustainability. The report includes, at no extra cost, a spreadsheet containing the data from the report and high-resolution presentation charts showing the key findings. It is the first in a 2-part series of reports, with the second report on building-to-grid interaction software being published later this year.

Both these reports are included in Memoori's 2024 Premium Subscription Service, which also gives access to our chatbot AIM, where you can query all our research using the power of Large Language Models (LLMs).

SAMPLE VIEW

HVAC Energy Management Solution Maturity Model

To better understand the landscape of HVAC energy management solutions and their relative maturity, Memoori has developed a model categorizing these solutions into four distinct tiers.

• Tier 1 represents basic energy monitoring and rule-based control, with limited automation and integration.
• Tier 2 introduces semi-automated control and basic data-driven analytics, allowing for more comprehensive energy management.
• Tier 3 transitions to data-driven optimization incorporating machine learning and predictive analytics, enabling dynamic optimization based on real-time and predictive data.
• Tier 4 represents the pinnacle of HVAC energy management, with predominantly autonomous and AI-driven systems capable of optimizing performance without human intervention.

Based on an assessment of available data on technology adoption, the report develops a theoretical model of the global distribution across the HVAC Energy Management Solution Maturity tiers.

Scope

This report focuses specifically on next-generation software solutions that leverage AI and IoT technologies to track, analyze, automate, and optimize HVAC energy consumption and performance. Software solutions included in the scope of the research for this report include:

• Software solutions directly supporting HVAC automation and optimization.
• Energy performance optimization and carbon emissions reduction solutions.
• Automated HVAC fault detection & diagnostics solutions.
• Data integration and interoperability solutions integral to HVAC optimization.
• AI-enabled occupancy-based HVAC control solutions.

Technology out of the scope of this report includes, broader energy management systems incorporating non-HVAC elements, energy data visualization and reporting tools, sustainability or ESG solutions, grid interaction software, and any hardware revenues related to energy management.

WITHIN ITS 227 PAGES AND 19 CHARTS, THE REPORT FILTERS OUT ALL THE KEY FACTS AND DRAWS CONCLUSIONS, SO YOU CAN UNDERSTAND EXACTLY HOW ENERGY MANAGEMENT TECHNOLOGY IS IMPACTING HVAC SYSTEMS AND WHY;

• The market for Energy Management Software for HVAC Optimization in Commercial Buildings is projected to grow from a baseline value of $3.65 billion in 2023 to $5.83 billion by 2029, representing a compound annual growth rate (CAGR) of 8.1%. Our projection accounts for regional disparities in adoption rates, macroeconomic influences, and technology-driven shifts to deliver a comprehensive and realistic market outlook.
• Data centers account for an outsized proportion of market revenues relative to their floorspace, representing 11.4% of overall HVAC optimization software revenues ($449 million) in 2024. HVAC cooling can account for up to 40% of a data center's total energy use, making efficient HVAC management crucial. AI-driven HVAC solutions in data centers can dynamically adjust cooling outputs based on real-time data such as server load levels, external weather conditions, and internal temperatures.
• The market for Energy Management Software for HVAC Optimization in Commercial Buildings is poised for significant growth over the next five years, driven by technological advancements, regulatory pressures, and increasing awareness of the need for energy efficiency.

This report provides valuable information to companies so they can improve their strategic planning exercises AND look at the potential for developing their energy management software business. The final part of the report provides a thorough competitive landscape analysis, profiling key players, market leaders, and emerging startups. This includes an overview of strategic partnerships, mergers, and acquisitions in the sector.

SAMPLE VIEW

The infographic above visualizes the flows of data that occur between different technologies to enable the AI HVAC Optimization Technology Stack. By integrating AI, IoT, and data analytics, this system can dynamically enhance HVAC performance, reflecting the core concepts discussed in this report.

WHO SHOULD BUY THIS ENERGY MANAGEMENT REPORT?

The information contained in this report will be of value to all those engaged in managing, operating, and investing in Commercial Buildings (and their Advisors) around the world. The report aims to help stakeholders make informed decisions that will drive the future of HVAC optimization and energy management.

Energy Management Software Companies Mentioned INCLUDE (but NOT limited to):

Table of Contents

Preface

Research Scope

Methodology

Definitions

1. Introduction

• 1.1. The Evolution of Building Energy Management Systems (BEMS)
• 1.2. Factors Influencing Energy Consumption in HVAC

2. Core Technologies

• 2.1. Sensors, Connected Devices, and IoT
• 2.2. Analytics, AI & Machine Learning
• 2.3. Edge and Cloud Computing
• 2.4. The AI-Enabled HVAC Optimization Technology Stack

3. The Current State of Energy Management in Commercial Buildings

• 3.1. Overview of Energy Consumption in Commercial Buildings
• 3.2. Energy Use Patterns in Commercial Buildings
• 3.3. Carbon Emissions from Commercial Building
• 3.4. Technology Adoption Rates
• 3.5. HVAC Energy Management Solution Maturity Model

4. Key Use Cases and Applications

• 4.1. Energy Performance Improvements
• 4.2. Carbon Emissions Reduction
• 4.3. Predictive Maintenance and Fault Detection
• 4.4. Occupancy-Based HVAC Control
• 4.5. Seasonal and Weather-Driven Optimization
• 4.6. Indoor Air Quality (IAQ) and HVAC Optimization

5. Vertical Market Applications & Opportunities

• 5.1. Vertical Market Overview
• 5.2. Offices
• 5.3. Retail
• 5.4. Hospitality & Food Services
• 5.5. Warehouses
• 5.6. Data Centers

6. Market Trends & Drivers

• 6.1. Global Energy Landscape
• 6.2. Renewables and the Energy Transition
• 6.3. Building-to-Grid Integration
• 6.4. Regulatory and Policy Landscape
• 6.5. Economic Factors and Real Estate Trends
• 6.6. Changing Workplace Dynamics
• 6.7. Urbanization and Smart City Initiatives
• 6.8. Sustainability, ESG, and Green Financing
• 6.9. Certifications and Industry Standards

7. Challenges and Barriers

• 7.1. Financial Barriers
• 7.2. Integration with Legacy Systems
• 7.3. Skills and Workforce Barriers
• 7.4. Data Privacy and Security
• 7.5. Retrofit and Ageing Building Stocks

8. Global Market Forecasts 2024 to 2029

• 8.1. Global Market Forecasts
• 8.2. Market Breakdown by Vertical

9. Regional Market Breakdown & Analysis

• 9.1. Regional Market Breakdown
• 9.2. Region Specific Market Drivers & Barriers

10. The Competitive Landscape in AI-Enabled HVAC Software

• 10.1. Regional Distribution of Companies
• 10.2. Distribution of Companies by Size
• 10.3. Distribution of Companies by Age

11. The Strategic Positioning of Key Players

• 11.1. Building Automation Firms
• 11.2. HVAC Specialists
• 11.3. Innovative Startups and Emerging Players

12. Investment Trends and M&A

• 12.1. Mergers and Acquisitions
• 12.2. Partnerships & Alliances
• 12.3. Investments Summary
• 12.4. Geographic Investment Trends
• 12.5. Notable Investment Deals

List of Charts and Figures

• Fig 2.1 - Installed Base of IoT Devices in Commercial Smart Buildings 2020 - 2028 (Millions)
• Fig 2.2 - The Internet of Things in Smart Commercial Buildings 2023 v5.1
• Fig 2.3 - AI & Machine Learning Techniques and their Smart Building Applications
• Fig 2.4 - AI-Enabled HVAC Optimization Technology Stack
• Fig 3.1 - Share of Buildings in Total Final Energy Consumption and Global Energy Emissions in 2022
• Fig 3.2 - Major Fuels Consumption by End Use in US Commercial Buildings 2018
• Fig 3.3 - Total Final Energy Consumption in Buildings by Region 2010 to 2022
• Fig 3.4 - Share of U.S. Commercial Floorspace that Incorporates Selected Sensor and Control Technologies 2012 to 2050
• Fig 3.5 - HVAC Energy Management Solution Maturity
• Fig 4.1 - AI's Energy-Saving Potential by Application Area
• Fig 5.1 - HVAC Energy Intensity by Building Type in US Buildings 2018
• Fig 6.1 - Commercial Sector Construction Growth Estimates by Region 2024 to 2029
• Fig 8.1 - The Global Market for Energy Management Software for HVAC Optimization in Commerical Buildings 2023 to 2029
• Fig 8.2 - Energy Management Software for HVAC Optimization by Vertical Market 2024
• Fig 9.1 - Energy Management Software for HVAC Optimization by Region 2024 to 2029
• Fig 10.1 - Regional Distribution of HVAC Optimization Software Companies
• Fig 10.2 - Distribution of HVAC Optimization Software Companies by Size, Number of Employees
• Fig 10.3 - Distribution of HVAC Optimization Software Companies by Age
• Fig 12.1 - Global Investment Landscape of HVAC Optimization Software Companies, Average Funding and Number of Funded Companies in Leading Countries