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유틸리티 및 에너지 분석 시장 : 성장, 동향, 예측(2019-2024년)

Utility and Energy Analytics Market - Growth, Trends, COVID-19 Impact, and Forecasts (2021 - 2026)

리서치사 Mordor Intelligence Pvt Ltd
발행일 2021년 01월 상품 코드 547076
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유틸리티 및 에너지 분석 시장 : 성장, 동향, 예측(2019-2024년) Utility and Energy Analytics Market - Growth, Trends, COVID-19 Impact, and Forecasts (2021 - 2026)
발행일 : 2021년 01월 페이지 정보 : 영문

본 상품은 영문 자료로 한글과 영문목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문목차를 참고해주시기 바랍니다.

유틸리티 및 에너지 분석 시장은 2018년 2억 8,680만 달러를 기록했습니다. 시장은 2019-2024년간 24.9%의 연평균 복합 성장률(CAGR)로 성장할 전망이며, 2024년에는 9억 8,550만 달러에 달할 것으로 예측됩니다.

세계의 유틸리티 및 에너지 분석(Utility and Energy Analytics) 시장에 대해 조사했으며, 시장 동향과 기회, 성장 촉진요인 및 저해요인, 설치·종류·용도·지역별 시장 분석, 경쟁 구도, 주요 기업 개요 등의 정보를 제공합니다.

목차

제1장 서론

  • 조사 성과
  • 조사의 전제조건
  • 조사 범위

제2장 조사 방법

제3장 주요 요약

제4장 시장 역학

  • 시장 개요
  • 시장 성장 촉진요인 및 저해요인 서론
  • 시장 성장 촉진요인
    • 에너지 수요 증가 및 환경에 대한 관심 고조
    • 에너지 소비 패턴 분석에 대한 소비자의 관심 고조
  • 시장 성장 저해요인
    • 시장 성장 과제에 대한 보안상 우려 및 호환성 문제
  • 밸류체인 분석
  • 업계의 매력 - Porter's Five Forces 분석
    • 신규 참여업체의 위협
    • 구매자/소비자의 협상력
    • 공급업체의 협상력
    • 대체 제품의 위협
    • 업계내 경쟁

제5장 시장 세분화

  • 설치별
    • 클라우드
    • 온프레미스
    • 하이브리드 클라우드
  • 종류별
    • 소프트웨어
    • 서비스
  • 용도별
    • 미터 조작
    • 부하 예측
    • 수요반응
    • 유통 계획
    • 기타
  • 지역별
    • 북미
    • 유럽
    • 아시아태평양
    • 남미
    • 중동 및 아프리카

제6장 경쟁 구도

  • 기업 개요
    • Oracle Corporation
    • Capgemini SE
    • ABB Corporation
    • IBM Corporation
    • CA Technologies
    • SAS Institute Inc.
    • Siemens AG
    • Schneider Electric SE
    • SAP SE
    • BuildingIQ Inc.
    • Teradata Corporation

제7장 투자 전망

제8장 시장 기회 및 향후 동향

LSH 19.08.02

The utility and energy analytics market was valued at USD 358.2 million in 2020 and is expected to reach USD 1372.6 million by 2026, at a CAGR of 24.9% over the forecast period 2021 - 2026. With the increase in the usage of the microgrids control system and other smart grid systems, which enables companies to monitor, control, and analyze grid functioning from a central control center, there is a vast untapped potential of advanced analytics tools and techniques, such as the big data platform and cloud computing. The favorable government regulations promoting smart grid solutions and exponentially increasing adoption of smart meters are also expected to drive the demand for big data analytics among utility vendors.

  • The use of electric vehicles (EVs) is growing, with the International Energy Agency (IEA) predicting that the number of electric cars on the road will increase from 3.1 million in 2017 to 125 million by 2030. It gives opportunity to the utilities vendors such that they can intelligently manage the new energy demand on the power grid.
  • The utility company are significantly investing to deploy smart meters across varius region. For instance, the Chinese State Grid Corporation planned to install 380 million smart meters in the country by 2020. Due to these factors, the market studied has a huge opportunity over the forecast period.
  • Software segment, which comprises of risk analytics, asset management analytics, grid analytics, and other such analytics, is projected to hold its market position during the forecast period. With the help of big data, utility companies are not only understanding the customer consumption patterns but also in managing technical challenges, such as dispatch ability and load matching.
  • Morever, government initiatives, such as the EU's Energy Performance of Buildings Directive (EPBD) and the US Commercial Building Initiative (CBI), are forcing public authorities and businesses to step up their efforts to limit greenhouse gas emissions and energy consumption at the community level.​
  • Further, renewable energy is another important component that can benefit from big data analytics. Renewable energy technologies are gaining acceptance, globally, primarily as a reliable source of electricity. According to IEA, renewable energy capacity is expected to expand by 43% or more than 920 giga watt by 2022. Furthermore, solar energy is expected to continue to dominate the renewables market, generating far more electricity in the next four years than wind and hydropower.
  • With analytics solutions, energy utilities can optimize power generation and planning. The renewable energy sector is encouraging the adoption of analytics. Predictive analytics, when used on renewable energy power plants, can provide accurate energy production forecast. It predicts the machine glitches. Thus, optimizing operational efficiencies. ​
  • For instance, IBM's hybrid renewable energy forecast technique uses big data, predictive analysis, and weather modeling technology to predict the variable resources for solar and wind power generation. This can increase the amount of renewable power generation integrated into the grid by 10%, which can power additional 14,000 homes. ​
  • Owing to the recent outbreak of Covid-19,multiple governments across the globe are increasingly limiting the movement of people primarily to slow down the spread of virus, utilities and the energy sector may expect a shift in the demand for electricity. The residential consumption and demands on water infrastructure is also expected to witness an increase as people are at home for longer periods of time. The usage of analytics solutions will primarily help these companies to better forecast the demand response and make accurate distribution planning.
  • Also,with COVID-19 crisis having a major impact in the utility and energy sector, it is likely that most of the existing company suppliers are having challenges to fulfil the urgent requirements. Industries are still adjusting to the COVID-19 economy, from new internal logistics like WFH or building out infrastructure to cope up with new demand. Moreover, many of the heaviest spending reductions are being felt in the industries which were hardest hit by the effect of COVID-19. ​

Key Market Trends

Two-way Communication between Smart Meters and Utilities Enables Inreased Application

  • Electricity cannot be stored in large volumes and supply and demand must be matched to achieve a balanced system. Predictive analytics plays an important role in accurately forecasting these demands.
  • The deployment of advanced metering infrastructure (AMI) by utilities have enabled electricity usage sensing and bi-directional communication between consumers and electric utilities. This provides ample opportunities to efficiently deal with peak demands and reduce energy consumption by using pricing incentives as in demand response (DR) programs.
  • Demand response provides an opportunity for consumers to play a significant role in the operation of the electric grid, by reducing or shifting their electricity usage during peak periods in response to time-based rates or other forms of financial incentives.
  • The growing availability of high resolution, high-dimensional electricity consumption data offers unique opportunities in developing forecasting models. But this has also offered a data repository for data analytics for balancing the supply and demand. Such models can lower the cost of electricity in wholesale markets, and in turn, lead to lower retail rates.
  • In February 2020,Energy Efficiency Services Limited (EESL) completed the installation of 10 lakh smart meters across India under the Government of India's Smart Meter National Programme. EESL has set the target to install 25 crore smart meters over the course of next few years.

North America to Lead and Pioneer Market for Utility and Energy Analytics Solutions

  • North America is one of the leading adopters of analytics solutions and is considered to be one of the largest markets for utility and energy analytics. The demand in the region is mainly driven by a higher focus on innovations through R&D and technology advancement in developed economies, such as the United States and Canada. The region's large consumption of energy is also supporting the growth of the market. Moreover, the region has a strong foothold of vendors in the market. Some of them include IBM Corporation, Oracle Corporation, BuildingIQ, and SAS Institute Inc among others.
  • Moreover, the US government is upgrading its energy grids and upgrading to Advanced Metering Infrastructure (AMI) to reduce energy consumption. For instance, according to EIA, US Energy Information Administration, the residential sector observed the highest number of AMI adoption in the country. During fiscal 2018-2019, the residential sectors adopted 118.27 million AMI whereas the commercial sector adopted 15.3 million.​
  • According to the US Energy Information Administration, the total energy consumption is expected to increase by 5% between 2016 and 2040. With such less growth, it is essential for companies to reduce downtime to maintain profitability efficiently. This fuels the market for data analytics in utilities and energy.
  • The penetration of smart meters in Canada is high owing to ambitious initiatives undertaken by the country in its most populous provinces. Further, the large number of smaller cooperative and municipal utilities are also expected to play a key role in market penetration.​
  • According to the Institute for Electric Efficiency, yearly shipments of smart electricity meters in the US will grow from 61 million units in 2015 to 90 million units in 2024. Over the next few years, smart meters deployments by various companies such as Consolidated Edison, Duke Energy, Ameren, Entergy, PSEG, National Grid, and Xcel Energy are expected to boost the shipments of smart meters.​

Competitive Landscape

The utility and energy analytics market is highly competitive and consists of several major players. These major players,, with a prominent presence in the market,, are focusing on expanding their customer base across the market segments. The companies are leveraging strategic collaborative initiatives to increase their market share and improve profitability. The companies operating in the market are also acquiring or partnering with start-ups working on utility and energy analytics technologies to strengthen their product capabilities and introduce new features.

  • February 2020 - mCloud Technology Corporation has signed an Expression of Interest to acquire BuildingIQ to integrate new AI and IoT solutions into AssetCare, which would combine it's energy savings technologies to target new large commercial spaces such as hospitals and bring new energy management tactics such as automated measurement and verification.
  • September 2019 - Agentis and Oracle Utilities Opower have collaborated to help utility companies to engage and drive energy savings for every customer by combining Agentis' software in the utility business segment with Oracle's leading customer engagement and energy efficiency solutions. The utility company will be able to actively connect with each type of customer with personalized insights that drive action and verified energy savings.
  • May 2019 - Tapping deep machine learning, Oracle Utilities Analytics Insights has been able to identify the presence of an EV, show the time and frequency of charging, and disaggregate the energy being consumed by the vehicle with advanced metering infrastructure (AMI) data. With this intelligence, utilities can reliably plan for the energy infusion needed to power EVs at scale and engage customers to charge at the times that are the least expensive for them and best for the health of the energy grid. The new EV detection capabilities from Oracle Utilities Analytics Insights are currently being piloted by a number of utilities.

Reasons to Purchase this report:

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

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Deliverables
  • 1.2 Study Assumptions
  • 1.3 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET DYNAMICS

  • 4.1 Market Overview
  • 4.2 Introduction to Market Drivers and Restraints
  • 4.3 Market Drivers
    • 4.3.1 Rising Demand for Energy and Increasing Emphasis on a Greener Environment
    • 4.3.2 Growing Consumer Focus on Energy Consumption Pattern Analysis
  • 4.4 Market Restraints
    • 4.4.1 Compatibility Issues and Skill Gap
    • 4.4.2 Security Concerns
  • 4.5 Industry Attractiveness - Porter's Five Force Analysis
    • 4.5.1 Threat of New Entrants
    • 4.5.2 Bargaining Power of Buyers/Consumers
    • 4.5.3 Bargaining Power of Suppliers
    • 4.5.4 Threat of Substitute Products
    • 4.5.5 Intensity of Competitive Rivalry

5 MARKET SEGMENTATION

  • 5.1 By Deployment
    • 5.1.1 Cloud
    • 5.1.2 On-premise
  • 5.2 By Type
    • 5.2.1 Software
    • 5.2.2 Services
  • 5.3 By Application
    • 5.3.1 Meter Operation
    • 5.3.2 Load Forecasting
    • 5.3.3 Demand Response
    • 5.3.4 Distribution Planning
    • 5.3.5 Other Applications
  • 5.4 Geography
    • 5.4.1 North America
    • 5.4.2 Europe
    • 5.4.3 Asia-Pacific
    • 5.4.4 Latin America
    • 5.4.5 Middle East & Africa

6 COMPETITIVE LANDSCAPE

  • 6.1 Company Profiles
    • 6.1.1 Oracle Corporation
    • 6.1.2 Capgemini SE
    • 6.1.3 ABB Corporation
    • 6.1.4 IBM Corporation
    • 6.1.5 General Electric Company
    • 6.1.6 SAS Institute Inc.
    • 6.1.7 Siemens AG
    • 6.1.8 Schneider Electric SE
    • 6.1.9 SAP SE
    • 6.1.10 Teradata Corporation

7 INVESTMENT ANALYSIS

8 MARKET OPPORTUNITIES AND FUTURE TRENDS

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