能源产业巨量资料分析：市场占有率分析、产业趋势与统计、成长预测（2024-2029）

能源产业巨量资料分析市场预计将从 2024 年的 93.1 亿美元成长到 2029 年的 158.9 亿美元，预测期（2024-2029 年）复合年增长率为 11.28%。

巨量资料分析在能源领域降低能源消费量和提高能源效率方面发挥重要作用，导致产业对分析的需求不断增加。

主要亮点

• 石化燃料的稀缺导致人们越来越依赖太阳能、波浪涡轮机和风力发电机等替代能源，消费量迅速增加。因此，使用先进的大资料库分析工具来了解这些能源来源的行为和适应变得至关重要。油价波动导致能源相关计划的高支出，并创造了对巨量资料分析的需求。因此，对优质资讯的需求不断增加，这可能会增加市场成长和盈利。
• 能源产业面临许多挑战，包括预测生产需求、提高效率、负载平衡和优化以及优化营运流程。虽然英国石油公司和哈里伯顿等许多大公司已经实施了资料分析，但小型和资料匮乏的公司仍有很大潜力达到新的高度。巨量资料分析提供一致的、资料支援的输出，有助于避免停机和供应链中断。
• 一些服务供应商共同提供有效的分析服务。 2022 年 9 月，斯伦贝谢和 Cognite 宣布建立策略合作伙伴关係，将斯伦贝谢的地下企业资料解决方案与 Cognite 的开放式工业 DataOps 平台 Cognite Data Fusion 整合。这项合作关係将使客户能够将油井、油藏和设施的资料整合到开放平台中，​​利用内建人工智慧和先进的分析工具来优化生产、降低成本并减少营运空间。它将是这样的。
• 然而，最近爆发的COVID-19清楚地表明，不确定性对决策流程和市场产生负面影响。随着市场参与企业开始接收有关情况的即时讯息，能源市场开始放缓。在这种场景下使用巨量资料可以将资讯放大到各个相关人员，防止恐慌，确保市场稳定和供应安全。
• 此外，人们对智慧电錶优势的认识不断提高，以及对替代能源的投资增加，正在推动 COVID-19 大流行后的市场扩张。此外，石油价格波动、石化燃料枯竭以及电力传输效率和可靠性提高等新趋势也推动了能源领域对巨量资料分析的需求。此次疫情也凸显出缺乏训练有素、具备专业知识的劳动力，这限制了该产业的扩张。

能源产业巨量资料分析市场趋势

智慧电錶推动市场成长

• 巨量资料分析的智慧计量包括电网营运、资源规划、现场服务、客户体验和法规遵循等组件。它有助于透过产生的资料增强需求和预测，这可能会推动市场成长。
• 此外，智慧电錶巨量资料分析有助于预测能源消耗。这在管理供需和减少能源浪费方面发挥关键作用。根据英国商业、能源和工业战略部（BEIS）2022年3月发布的报告，近期总合安装了380万个智慧电錶，与前一年同期比较增加了7%。此外，根据官方决议，哥伦比亚政府希望在 2030 年为 75% 的家庭安装智慧电錶。
• 此外，大量的智慧电錶部署会产生大量资料。例如，如果智慧电錶每30分钟记录一次资料，那么2000万隻智慧电錶在短短一年内产生的记录数将是3.51011笔。此外，智慧电錶资料（消费量、故障、断电、价格资讯等）的多样性和性质产生异质多源资料。这样，智慧电錶资料就具备了巨量资料量大、异质性高等特性。此外，智慧电錶资料必须快速处理和分析，以便于即时分析。根据能源效率研究所的数据，2022 年美国将安装 1.24 亿个智慧电錶，比前一年略有增加。
• 此外，需要脱碳和去中心化的公共产业可以透过添加地理资讯系统 (GIS)、CIS 和天气资料等其他资讯来源，从计量资料中受益。 AWS 快速入门在 AWS 云端上部署智慧电錶资料分析 (MDA) 平台。该平台帮助公用事业公司利用能源消耗资料的价值，同时消除麻烦。该平台还使公用事业公司能够提供新服务，例如负载预测、透过主动通知更深入地与客户参与、配电资产的预测性维护以及线路品质分析。
• 根据业务环境，各个作业系统可以将资料传送到平台以获得可操作的见解。例如，根据AWS报告，Kalkitech是AWS精选技术合作伙伴，提供电錶通讯解决方案，包括用于抄表应用程式的通讯协定堆迭、大型电錶模拟器和电錶测试工具。该公司根据监管机构的要求提供这些工具，并提供智慧电錶作为云端基础的服务。
• MDA平台每天可批次处理高达250TB的抄表资料。它还处理迟到的资料，并为各种消费端点资料准备，例如资料仓库 (Amazon Redshift)、机器学习管道 (Amazon SageMaker) 或 API，从而允许将资料传送到第三方应用程式。 。
• 新兴国家正在能源领域大力投资，由先进巨量资料技术驱动的智慧电錶普及在未来几年将更加普及。此外，Ameren 还与密苏里州监管机构制定了一项策略，扩大其智慧型能源计画 (SEP)，到 2025 年安装 120 万个智慧电錶，并最近购买了两个总合700 MW 的风电场。我提案。

亚太地区市场成长显着

• 该地区对所研究市场的成长做出了重大贡献。该地区的巨量资料分析市场正在稳步增长，这主要是由于包括中国和印度在内的多个国家越来越多地采用物联网和智慧技术，以及智慧城市等各种政府倡议，这一点已得到证实。在能源领域。根据电力部国家智慧电网任务近期发布的资料，截至2022年1月，印度各邦智慧电网总配额1,116万台中，已安装373万台。 EESL 的目标是取代 250 亿个传统设备。印度正在透过智慧电錶国家计画 (SMNP) 将电錶与智慧电錶连接起来，以减少 AT&C 损失。
• 在亚太地区，由于中国人口众多，智慧电錶和创新电网系统的适应率不断提高，中国有望成为能源和公共产业领域巨量资料分析的重要国家。根据彭博社报道，2022年5月，中国政府报告​​称，2022年前四个月在太阳能和风能计划等清洁能源计划上投资约43亿美元，高于2021年同期金额。与同期投资相比约204 %。有前景的投资预计将吸引一代人的智慧电錶和相关计划，进一步吸引该国多个最终用户的消费，并推动对巨量资料分析的需求，以充分利用资源。
• 此外，该地区的发电业也有大量活动。与全球趋势一致，该产业积极推出绿色发电解决方案，特别是在印度、中国、日本和新加坡等国家。
• 在日本，电力公司已开始实施国家电网重组计划，这将需要对输配电设备和基础设施进行投资。鑑于核能发电厂除役，日本政府加大了对可再生能源的关注。政府的目标是到2030年25-35%的电力来自可再生能源。
• 同时，根据Utility Bidder称，新加坡比其他国家都更依赖石化燃料，正在利用先进的计量系统加速向清洁能源的过渡。根据《Smart Energy International》发表的报告，新加坡最近仅安装了 50 万个智慧电錶，计划到 2024 年达到 140 万个。
• 市场上的各个参与者正在扩大其产品范围，并利用印度城市发展的需求。例如，ABB 印度公司于 2022 年 2 月针对数位面板电錶市场推出了最新系列的电力测量和电力监控电錶，2017 年至 2023 年全球复合年增长率为 6%。透过此次推出，除了现有的单一网​​路分析仪和多功能仪表之外，ABB 印度还提供了广泛的产品组合，以满足医疗保健、基础设施、饭店和餐饮等行业的面板仪表市场需求。

能源领域巨量资料分析的产业概述

能源产业巨量资料分析市场整合，大型企业占市场占有率。缺乏熟练的劳动力（具有分析技能和专业知识）、隐私问题日益严重以及资料外洩等因素使得新进入者难以进入市场。市场渗透率的提高和新技术投资能力的增强预计将加剧竞争对手之间的敌意。

其他福利

• Excel 格式的市场预测 (ME) 表
• 3 个月分析师支持

目录

第一章 简介

• 研究假设和市场定义
• 调查范围

第二章调查方法

• 调查系统
• 二次调查
• 初步调查
• 对资料进行三角测量并产生见解

第三章执行摘要

第四章市场动态

• 市场概况
• 市场驱动因素
  • 海量资料涌入
  • 原油价格波动
• 市场限制因素
  • 缺乏技术纯熟劳工
• 产业吸引力－波特五力分析
  • 供应商的议价能力
  • 买方议价能力
  • 新进入者的威胁
  • 替代产品的威胁
  • 竞争公司之间的敌意强度
• 评估 COVID-19 对产业的影响

第五章市场区隔

• 按用途
  • 电网营运
  • 智慧电錶
  • 资产和员工管理
• 按地区
  • 北美洲
  • 欧洲
  • 亚太地区
  • 拉丁美洲
  • 中东和非洲

第六章 竞争形势

• 公司简介
  • IBM Corporation
  • Siemens AG
  • SAP SE
  • Dell Technologies Inc.
  • Accenture PLC
  • Infosys Limited
  • Intel Corporation
  • Microsoft Corporation
  • Palantir Technologies Inc.
  • Enel X Srl

第七章 投资分析

第八章市场的未来

The Big Data Analytics Market In Energy is expected to grow from USD 9.31 billion in 2024 to USD 15.89 billion by 2029, at a CAGR of 11.28% during the forecast period (2024-2029).

Big Data analytics plays a crucial role in reducing energy consumption and improving energy efficiency in the energy sector, thus boosting the demand for analytics in the industry.

Key Highlights

• The scarcity of fossil fuels is increasing the dependency on alternate energy sources, such as solar, wave, and wind turbines, where consumption is rising rapidly. Thus, it has become imperative to use advanced big data-based analytical tools to understand the behavior or adaption of these energy sources. The volatility in oil prices leads to high expenditure on energy-related projects, creating demand for big data analytics. Thus, the need for quality information is increasing, which may boost the market's growth and profitability.
• The energy sector faces many problems like predicting production demand, enhancing efficiency, optimizing load distribution and optimization, and optimizing operational processes. Many large corporates like BP and Halliburton have adopted data analytics, while there is a high scope for small companies with lesser data to achieve new heights. Big data analytics helps deliver consistent and data-backed outputs to avoid downtime or supply chain disruption.
• Some service providers collaborate to deliver effective analytics services. In September 2022, Schlumberger and Cognite announced entering a strategic partnership to integrate Schlumberger's Enterprise Data Solution for subsurface with Cognite's open industrial DataOps platform, Cognite Data Fusion. The partnership would allow customers to integrate data from wells, reservoirs, and facilities in a single, open platform and leverage embedded AI and advanced analytics tools to optimize production, reduce costs and decrease operational footprint.
• However, the recent COVID-19 outbreak revealed the negative impacts of uncertainty on decision-making processes and markets. When market participants started receiving real-time information about the situation, the energy markets began to ease. Big Data can be used in such scenarios to amplify information to various stakeholders to prevent panic and ensure market stability and security of supply.
• Also, after the COVID-19 pandemic, the growing awareness of the benefits of smart metering and increased investment in alternative energy sources are driving market expansion. Furthermore, the volatility of oil prices, the depletion of fossil fuels, and emerging trends for improved efficiency and dependability in power transmission contribute to the demand for Big Data analysis in the energy sector. The pandemic also highlighted the shortage of trained labor with domain-specific knowledge limiting industry expansion.

Big Data Analytics in Energy Sector Market Trends

Smart Metering to Fuel Market Growth

• Smart metering in Big Data analytics contains components such as grid operations, resource planning, field services, customer experience, and regulatory compliances. It helps enhance demand and forecast through the data generated, which will likely boost market growth.
• Furthermore, Big Data analytics in smart metering assists in predicting energy consumption, which plays a vital role in managing demand and supply and mitigates the waste of energy. According to the UK Department of Business, Energy and Industrial Strategy (BEIS) report published in March 2022, a total of 3.8 million smart meters were installed recently, with a 7% increase from the previous year. In addition, in Colombia, the government desires to have 75% of households with smart meters til 2030, according to an official resolution.
• Further, the large number of smart meters deployed can generate tremendous data. For example, if an intelligent meter records data every half hour, the number of records generated by twenty million intelligent meters is 3.51011 over just one year. Further, the diversity and nature of smart meter data (e.g., consumption, fault, outage, and price information) results in heterogeneous multi-source data. Thus, smart meter data has the characteristics of big data, such as large volumes and high heterogeneity. In addition, intelligent meter data must be quickly processed and analyzed to facilitate real-time analysis. According to the Institute for Electric Efficiency, 124 million smart meters installed in 2022 in the United States, a slightly increased from the previous year.
• Moreover, utilities that require decarbonization and decentralization can benefit from metering data by adding other information sources like geographic information systems (GIS), CIS, and weather data. AWS Quick Start deploys the Smart Meter Data Analytics (MDA) platform on AWS Cloud. This platform helps the utilities tap the value of energy consumption data while removing heavy lifting. The platform also allows utilities to provide new services such as load prediction, deeper customer engagement through proactive notifications, predictive maintenance on distribution assets, and circuit quality analytics.
• Depending on the business context, the individual operating systems can send data to the platform and get actionable insights. For example, According to a report by AWS, Kalkitech is an AWS Select Technology Partner, providing meter communication solutions such as a protocol stack for meter reading applications, a large-scale meter simulator, and a meter test tool. The company offers these tools per the regulatory bodies, providing smart metering as a cloud-based service.
• The MDA platform can process up to 250TB of meter reads daily in batches. It also handles late-arriving data and prepares data for different consumption endpoints like a data warehouse (Amazon Redshift), a machine learning pipeline (Amazon SageMaker), or APIs to make the data consumable for third-party applications.
• Developing countries are hugely investing in the energy sector, which is expected to boost smart metering with advanced Big Data techniques in the coming years. Additionally, Ameren proposed expanding its Smart Energy Plan (SEP) with Missouri regulators, laying out a strategy to install 1.2 million smart meters by 2025 and purchasing two wind farms totaling 700 MW recently.

Asia Pacific\sto Experience Significant Market Growth

• The region is contributing significantly to the studied market growth. Primarily due to the factors, such as the increasing adoption of IoT and smart technologies and various government initiatives, such as smart cities, across multiple countries, including China and India, affirm the region as the favorably-growing region in the Big Data analytics market in the energy sector. According to the recent data released by the National Smart Grid Mission, Ministry of Power, out of the total allocated quantity of 11.16 million smart meters, 3.73 million were installed across various states in India as of January 2022. EESL aimed to replace 25 crore conventional meters with smart meters in India through the Smart Meters National Program (SMNP) to reduce AT&C losses.
• In the Asia-Pacific, China is expected to be a significant country in Big Data analytics in the energy and utility sector due to its immense population and rising rate of adaptation of smart metering and innovative grid systems. According to Bloomberg, in May 2022, the Chinese government reported having invested around USD 4.3 Billion in clean power projects like solar and wind projects in the first fourth months of 2022, about 204% compared to the investment in the same period in 2021. Such promising investments will attract smart metering and related projects at the generation level and for further consumption to several end-users in the country, propelling the demand for big data analytics for the best utilization of the resources.
• Additionally, there has been significant high activity in the region's power generation sector. Similar to the global trend, there has been immense activity in the industry to adopt greener power generation solutions, especially in countries like India, China, Japan, and Singapore.
• In Japan, electrical utilities have begun implementing a nationalized grid restructuring program, which would necessitate investment in T&D equipment and infrastructure. Given the country's decommissioning of nuclear power plants, the Japanese government is increasing its focus on renewable energy. The government is working towards generating 25-35% of power from renewable sources by 2030.
• At the same time, according to Utility Bidder, Singapore, which relies on fossil fuels more than any other country, is leveraging advanced metering to speed up the shift to clean energy resources. According to a report published in Smart Energy International, Singapore has only installed 500,000 smart meters recently and plans to reach the 1.4 million mark by 2024.
• Various players in the market are increasing their product range and scope to capitalize on the demand in the Indian urban development landscape. For instance, in February 2022, ABB India launched the latest series of electrical measuring and power monitoring meters for the digital panel meter market, registering a CAGR of 6% between 2017-2023 globally. With this introduction, ABB India offerings a broad portfolio in addition to the existing range of single network analyzers and multifunction meters catering to the Panel Meter market across industries such as healthcare, infrastructure, hospitality, and F&B, to name a few.

Big Data Analytics in Energy Sector Industry Overview

The Big Data analytics market in the energy sector is consolidated, with major players dominating the market share. Due to factors a lack of skilled workforce (with analytical skills and expertise), rising privacy concerns, and data breaches, new players are finding it difficult to enter the market. The competitive rivalry is anticipated to be high due to higher market penetration and the ability to invest in new technologies.

In February 2022, cQuant.io, an energy analytics company, partnered with Microsoft to scale its cQuant energy analytics solution, enabling customers to decrease their greenhouse gas emissions with reliable renewable energy purchases.

In February 2022, IBM and SAP strengthened their partnership to help clients move workloads from SAP Solutions to the cloud. IBM announced teaming with SAP to provide technology and consulting expertise, making it easier for clients to embrace a hybrid cloud strategy and move mission-critical workloads from SAP Solutions to the cloud for regulated and non-regulated enterprises.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

• 2.1 Research Framework
• 2.2 Secondary Research
• 2.3 Primary Research
• 2.4 Data Triangulation and Insight Generation

3 EXECUTIVE SUMMARY

4 MARKET DYNAMICS

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Enormous Influx of Data
  • 4.2.2 Volatility in the Oil Prices
• 4.3 Market Restraints
  • 4.3.1 Lack of Skilled Labor
• 4.4 Industry Attractiveness - Porter's Five Forces Analysis
  • 4.4.1 Bargaining Power of Suppliers
  • 4.4.2 Bargaining Power of Buyers
  • 4.4.3 Threat of New Entrants
  • 4.4.4 Threat of Substitute Products
  • 4.4.5 Intensity of Competitive Rivalry
• 4.5 Assessment of the Impact of COVID-19 on the Industry

5 MARKET SEGMENTATION

• 5.1 By Application
  • 5.1.1 Grid Operations
  • 5.1.2 Smart Metering
  • 5.1.3 Asset and Workforce Management
• 5.2 By Geography
  • 5.2.1 North America
  • 5.2.2 Europe
  • 5.2.3 Asia-Pacific
  • 5.2.4 Latin America
  • 5.2.5 Middle-East and Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Company Profiles
  • 6.1.1 IBM Corporation
  • 6.1.2 Siemens AG
  • 6.1.3 SAP SE
  • 6.1.4 Dell Technologies Inc.
  • 6.1.5 Accenture PLC
  • 6.1.6 Infosys Limited
  • 6.1.7 Intel Corporation
  • 6.1.8 Microsoft Corporation
  • 6.1.9 Palantir Technologies Inc.
  • 6.1.10 Enel X S.r.l.

7 INVESTMENT ANALYSIS

8 FUTURE OF THE MARKET