このレポートは、スマートグリッドの採用を促進する主要動向、高度ITインフラ内の効率的な電源、導入のメリット、今後の展開における課題など、鋭い詳細分析と幅広い貴重な考察を提供しています。

 

Report　Description

Juniper Research’s latest Smart Grid research provides in-depth analysis and evaluation of how the requirements of the energy grid are rapidly changing, and how technology is rising to meet challenges by introducing advanced, AI-enabled analytics; promising potential benefits to smart grids. The report delivers critical and actionable insights on the state of digitalisation, key smart grid vendors driving the evolution of the market and their future prospects. The study contains the Juniper Research Competitor Leaderboard; positioning 18 key smart grid vendors.

 

The Smart Grid market research reports provide incisive and detailed analysis, and a wide range of valuable insights of the key trends driving smart grid adoption and efficient power sources within advanced IT infrastructure, benefits of deployments and challenges with further roll-outs. It also features a comprehensive forecast suite of the economic growth of technological advancements in the market; encompassing utility grid modernisation for the following key factors:

Smart grid adoption and the resulting software spend, energy savings and cost savings.

Smart metering adoption and the resulting shipments, hardware revenue and connectivity revenue.

This research suite comprises:

Market Trends & Strategies (PDF)

Competitor Leaderboard (PDF)

Data & Forecasts (PDF & Excel)

12 Months' Access to harvest Online Data Platform

 

Key Market Statistics

 

 

KEY FEATURES

Market Dynamics: Provides a detailed assessment of how the smart grid market share and market growth is evolving, what benefits it can deliver and what the barriers are to future growth within smart city projects in the energy sector.

Future Outlook & Regional Analysis: Future outlook and comprehensive analysis of the key countries and regions deploying smart grid technologies in smart grid network management, encapsulated by our future outlook for deployment.

Key Takeaways & Strategic Recommendations: Featuring major opportunities and crucial factors for smart grid vendors highlighted across the smart grid landscape; making for important reading for key stakeholders, including smart grid vendors, utility companies and governments.

Benchmark Industry Forecasts: 5-year forecasts are provided for smart grid adoption, software spend, energy savings and cost savings. Additionally, smart metering forecasts are included, such as the number of smart meters in service, the shipments of smart meters, hardware revenue, connectivity revenue, and connectivity splits, including 2G, 3G, 4G, 5G, LTE-M (Long-term Evolution Machine-type Communication) and NB-IoT (Narrowband Internet of Things). The regional market revenue forecast data is also split by 8 forecast regions and 60 countries:

North America:

Canada, US

Latin America:

Argentina, Brazil, Chile, Colombia, Ecuador, Mexico, Peru, Uruguay

West Europe:

Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, UK

Central & East Europe:

Croatia, Czech Republic, Hungary, Poland, Romania, Russia, Turkey, Ukraine

Far East & China:

China, Hong Kong, Japan, South Korea

Indian Subcontinent:

Bangladesh, India, Nepal, Pakistan

Rest of Asia Pacific:

Australia, Indonesia, Malaysia, New Zealand, Philippines, Singapore, Thailand, Vietnam

Africa & Middle East:

Algeria, Egypt, Israel, Kenya, Kuwait, Nigeria, Qatar, Saudi Arabia, South Africa, United Arab Emirates

Juniper Research Competitor Leaderboard: Key player capability and capacity assessment for 18 smart grid vendors, via the Juniper Research Competitor Leaderboard featuring major players in smart grid systems:

 

 

KEY QUESTIONS ANSWERED

 

 

COMPANIES REFERENCED

Included in Juniper Research Competitor Leaderboard: ABB, CISCO Systems, Eaton, eSmart Systems, Fujitsu, General Electric, Honeywell, IBM Corporation, Itron, Landis+Gyr AG, Johnson Controls, Oracle Corporation, Panasonic Corporation, Robert Bosch GmbH, Schneider Electric, Siemens AG, Tantalus, Wipro.

 

Mentioned: Accenture, Aclara, Adobe, Airbus, Alibaba, Allmanna Svenska Elektriska Aktiebolaget, Alteryx, American Electric Power, Anthem, Appalachian Electric Coop, Arrow Electronics, Aspern Smart City Research, AT&T, AusNet Services, Avista Utilities, AWS (Amazon Web Services), Badger Meter, Baltimore Gas and Electric, BKW Group Switzerland, Blue Yonder, Boeing, BrightRidge Utility, Brown, Boveri & Cie, Carnegie Mellon University, Caterpillar, CenterPoint Energy, Chase Centre, Chevron, Cielis, Citrix Systems, Clevest, CLK Enerji, Cobham Mission Systems, Cognizant, ComEd, Commvault, Congruitive, CPS Energy, CVS, Dassault Systemes, Deloitte, Dropbox, Duke Energy Sustainable Solutions, E.ON, EDMI Limited, Enedis, Enel, Energy Queensland, Entegrus, EPB Chattanooga, EQUANS, Esri, Evergy, Exceleron, Exelon, Exxon Mobil, Fingrid, First Energy, Flexera, FogHorn, Fortinet, General Motors, Glitre Energi Nett, Google, Green Motion, Hewlett Packard, Intel, Itron, Jiangsu Yineng Electric, KAPES, Karnten Netz GmbH Austria, Keele University, Kentucky Utilities Company, Laclede Electric Coop, Lamb County EC, Lenovo, Lidl, Louisville Gas and Electric Company, Luna, Meta, Microsoft, Missouri University of Science and Technology, Mitnetz Storm, Mitsubishi Heavy Industries, Mongo DB, MySQL, National Grid, Naturgy Xcel Energy, Network Rail, NextGen Utility Solutions, NineStar Connect, Nissan, Northeastern REMC, Northern Ireland Electricity Networks, Oklahoma Gas and Electric Company, Oncor, Opus One, Philadelphia Museum of Art, Polaris, PTC, Pulaski Electric System, Qlik, Red Hat, Royal Power Solutions, Saint John Energy, Salesforce, SAP, Silver Spring Networks, Southern Company, Statnett, Stedin.net, Swiss Axpo, Tableau Software, Tampa Electric, Tata Consultancy Services, Telefonica, Tenable Network Security Inc, Tennet, Tesla, Thales, Tibco, TINT, Toshiba, Tripp Lite, True Energy, Upwork, UtiliSmart, Verico, Verizon, VMWare, Western Power Australia, Xcel Energy.

 

 

DATA & INTERACTIVE FORECAST

Juniper Research’s Smart Grid forecast suite includes:

?Smart grid adoption

Smart grid software spend

Energy savings and cost savings from smart grid adoption

Number of smart meters in service

Shipments of smart meters

Smart meter hardware revenue

Smart meter connectivity revenue

Smart meter connectivity splits, including 2G, 3G, 4G, 5G, LTE-M and NB-IoT

Geographical splits: 60 countries

Number of tables: 46 tables

Number of datapoints: Over 20,900 datapoints

 

harvest: Our online data platform, harvest, contains the very latest market data and is updated throughout the year. This is a fully featured platform enabling clients to better understand key data trends and manipulate charts and tables; overlaying different forecasts within the one chart ? using the comparison tool. Empower your business with our market intelligence centre, and receive alerts whenever your data is updated.

 

Interactive Excels (IFxl): Our IFxl tool enables clients to manipulate both forecast data and charts, within an Excel environment, to test their own assumptions using the interactive scenario tool and compare selected markets side by side in customised charts and tables. IFxls greatly increase a client’s ability to both understand a particular market and to integrate their own views into the model.

 

 

FORECAST SUMMARY

Cost savings from smart grid deployments will exceed $125 billion globally in 2027; increasing from just over $33 billion in 2022. This 279% growth will be driven by rising energy prices, with smart grid technologies playing a critical role in increasing network efficiency and optimising resource management. The abilities of AI-based analytics are crucial to maximising benefits of new renewable energy sources, by actively balancing load and optimising energy transmission.

Smart grid deployments are key to the decarbonisation of electricity production. Smart grids will enable energy sources that produce electricity based on external elements, such as solar and wind power, to meet energy requirements more effectively, by actively balancing load and predicting surges in demand & production.

By leveraging AI, electricity networks can ensure that spikes in demand are predicted and mitigated. Smart grid vendors must focus on enhancing their models to more accurately predict usage patterns to maximise these benefits.

Smart grid deployments will result in an almost 700 million MMT (Million Metrics Tons) reduction in CO2e (Carbon Dioxide Equivalent) emissions globally in 2027; falling from 214 million in 2022. This will be central to meeting stringent climate change goals, alongside updating generation capabilities to feature more renewable sources, including wind and solar.

Smart grid vendors must develop data ingestion engines that can analyse and interpret structured and unstructured data from disparate sources, including smart meters, network data and weather forecasts, to maximise emission reductions

 

1. Market Trends & Strategies

1. Key Takeaways & Strategic Recommendations

1.1 Key Takeaways . 4

1.2 Strategic Recommendations . 4

2. Smart Grid ? Market Landscape

2.1 Introduction . 7

Figure 2.1: Smart Grid Example. 8

Figure 2.2: Smart Grid Network Layer . 9

2.2 Key Areas in the Organisation of Smart Grid . 9

2.2.1 Networks in Smart Grid: . 9

i. Technologies/Networks Merging Communication Infrastructure for

Smart Grid . 10

2.2.2 Enabling Technologies & Devices . 10

2.2.3 Microgrid . 11

2.2.4 Smart Grid Software Architecture . 11

Figure 2.3: Smart Grid Technologies and Resources Across Systems . 11

2.3 The Benefits of Smart Grid Deployment . 11

Figure 2.4: Smart Grid Benefits . 12

2.4 Smart Metering Market Status . 14

Figure 2.5: Traditional Smart Metering Infrastructure . 14

2.5 Grid Battery Storage . 15

Figure 2.6: Grid Battery Storage Overview . 15

2.6 Challenges to Smart Grid Deployment . 16

3. Smart Grid: Regional Analysis and Future Outlook

3.1 Smart Grid: Regional Analysis and Future Outlook . 20

3.1.1 North America . 20

i. US . 20

Figure 3.1: Smart Meter Deployments by State, April 2022, as a Percentage of

Customers . 20

ii. Canada . 21

3.1.2 Latin America . 22

i. Brazil . 22

ii. Mexico . 23

3.1.3 West Europe . 24

i. Germany . 24

Figure 3.2: Installed Net Power Generation Capacity . 24

ii. Italy . 25

Figure 3.3: Gross Consumption of Electricity Generated by Renewable Sources,

2010-2020, Italy . 26

iii. UK . 27

3.1.4 Central & East Europe . 28

i. Poland . 28

Figure 3.4: Renewable Energy in Total Energy Consumption in Poland (2000-

2020) . 29

ii. Turkey . 30

3.1.5 Indian Subcontinent . 31

i. India . 31

3.1.6 Far East & China . 32

i. China . 32

ii. South Korea . 34

3.1.7 Japan. 35

Figure 3.5: Share of Renewables and Nuclear Power in Japan’s Electricity Supply

and Demand in 2021. 36

3.1.8 Rest of Asia Pacific. 37

i. Australia . 37

3.1.9 Africa & Middle East . 38

i. South Africa . 38

3.1.10 Israel . 39

3.1.11 Future Outlook of Smart Grid and Smart Meter Deployments . 40

 

 

2. Competitor Leaderboard

1. Competitor Leaderboard

1.1 Why Read This Report . 5

Table 1.1: Juniper Research Competitor Leaderboard: Smart Grid Vendors

Included & Product Portfolio . 6

Figure 1.2: Juniper Research Competitor Leaderboard: Smart Grid Vendors . 7

Table 1.3: Juniper Research Competitor Leaderboard: Smart Grid Vendors &

Positioning . 7

Table 1.4: Juniper Research Competitor Leaderboard Heatmap: Smart Grid

Vendors . 8

1.1.1 ABB . 9

i. Corporate . 9

ii. Geographical Spread . 9

iii. Key Clients & Strategic Partnerships . 9

iv. High-level View of Offerings . 9

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 10

1.1.2 CISCO Systems . 10

i. Corporate . 10

ii. Geographical Spread . 11

iii. Key Clients & Strategic Partnerships . 11

iv. High-level View of Offerings . 11

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 11

1.1.3 Eaton . 12

i. Corporate . 12

ii. Geographical Spread . 12

iii. Key Clients & Strategic Partnerships . 12

iv. High-level View of Offerings. 12

Figure 1.5: Brightlayer Suite Components . 13

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 13

1.1.4 eSmart Systems . 14

i. Corporate . 14

ii. Geographical Spread . 14

iii. Key Clients & Strategic Partnerships . 14

iv. High-level View of Offerings. 14

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 15

1.1.5 Fujitsu . 15

i. Corporate . 15

ii. Geographical Spread . 15

iii. Key Clients & Strategic Partnerships . 15

iv. High-level View of Offerings. 15

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 16

1.1.6 General Electric . 16

i. Corporate . 16

ii. Geographical Spread . 17

iii. Key Clients & Strategic Partnerships . 17

iv. High-level View of Offerings. 17

Figure 1.6: GE EnergyAPM Software . 18

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 18

1.1.7 Honeywell . 18

i. Corporate . 18

ii. Geographical Spread . 19

iii. Key Clients & Strategic Partnerships . 19

iv. High-level View of Offerings . 19

Figure 1.7: DemandSites Reporting and Analytics . 20

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 20

1.1.8 IBM Corporation . 20

i. Corporate . 20

ii. Geographical Spread . 21

iii. Key Clients & Strategic Partnerships . 21

iv. High-level View of Offerings . 21

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 22

1.1.9 Itron . 22

i. Corporate . 22

ii. Geographical Spread . 22

iii. Key Clients & Strategic Partnerships . 22

iv. High-level View of Offerings . 22

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 23

1.1.10 Landis+Gry AG . 23

i. Corporate . 23

ii. Geographical Spread . 24

iii. Key Clients & Strategic Partnerships . 24

iv. High-level View of Offerings . 24

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 25

1.1.11 Johnson Controls . 25

i. Corporate . 25

ii. Geographical Spread . 25

iii. Key Clients & Strategic Partnerships . 25

iv. High-level View of Offerings. 25

Figure 1.8: OpenBlue Platform . 26

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 27

1.1.12 Oracle Corporation . 27

i. Corporate . 27

ii. Geographical Spread . 27

iii. Key Clients & Strategic Partnerships . 27

iv. High-level View of Offerings. 27

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 28

1.1.13 Panasonic Corporation . 28

i. Corporate . 28

ii. Geographical Spread . 28

iii. Key Clients & Strategic Partnerships . 29

iv. High-level View of Offerings. 29

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 29

1.1.14 Robert Bosch GmbH. 30

i. Corporate . 30

ii. Geographical Spread . 30

iii. Key Clients & Strategic Partnerships . 30

iv. High-level View of Offerings. 30

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 31

1.1.15 Schneider Electric . 31

i. Corporate . 31

ii. Geographical Spread . 31

iii. Key Clients & Strategic Partnerships . 31

iv. High-level View of Offerings. 32

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 32

1.1.16 Siemens AG . 33

i. Corporate . 33

ii. Geographical Spread . 33

iii. Key Clients & Strategic Partnerships . 33

iv. High-level View of Offerings . 33

Figure 1.9: Siemens Xcelerator for Grids . 34

v. Juniper Research’s View: Strategic Recommendations & Key

Opportunities . 34

1.1.17 Tantalus . 35

i. Corporate . 35

ii. Geographical Spread . 35

iii. Key Clients and Strategic Partnerships . 35

iv. High-level View of Offerings . 35

v. Juniper Research’s View: Key Strengths & Strategic Development

Opportunities . 36

1.1.18 Wipro . 36

i. Corporate . 36

ii. Geographical Spread . 37

iii. Key Clients & Strategic Partnerships . 37

iv. High-level View of Offerings . 37

v. Juniper Research’s View: Key Strengths & Strategic Development

Opportunities . 38

1.2 Juniper Research Leaderboard Assessment Methodology . 39

1.2.1 Limitations & Interpretations . 39

Table 1.10: Juniper Research Competitor Leaderboard Factors . 40

 

 

3. Data & Forecasting

1. Market Overview & Methodology

1.1 Introduction . 3

1.2 Smart Grid: Forecast Methodology & Assumptions . 3

Figure 1.1: Smart Grid Forecast Methodology . 4

Figure 1.2: Smart Metering Forecast Methodology . 5

2. Smart Grid Market Forecasts

2.1 Introduction . 7

2.1.1 Smart Grid Software Revenue . 8

Figure & Table 2.3: Smart Grid Annual Software Spend ($m), Split by 8 Key

Regions, 2022-2027 . 8

2.1.2 Smart Grid Energy Savings . 9

Figure & Table 5.3: Smart Grid Energy Saving (TWh), Split by 8 Key Regions, 2022-

2027 . 9

2.1.3 Smart Grid Cost Savings . 10

Figure & Table 5.3: Total Smart Grid Energy & Emissions Cost Savings ($m), Split

by 8 Key Regions, 2022-2027 . 10

3. Smart Metering Market Forecasts

3.1.1 Introduction . 12

3.1.2 Smart Meters in Service. 13

Figure & Table 5.2: Smart Meters in Service (m), Split by 8 Key Regions, 2022-

2027 . 13

3.1.3 Smart Meter Shipments . 14

Figure & Table 5.2: Total Smart Meter Hardware Shipments (m), Split by 8 Key

Regions, 2022-2027 . 14

3.1.4 Smart Meter Hardware Revenue. 15

Figure & Table 5.2: Total Hardware Revenue from Smart Meters ($m), Split by 8

Key Regions, 2022-2027 . 15

3.1.5 Smart Meter Connectivity Revenue . 16

Figure & Table 5.2: Total Connectivity and Enablement Revenue for Smart

Metering ($m), Split by 8 Key Regions, 2022-2027 . 16

3.1.6 Smart Meter Total Revenue . 17

Figure & Table 5.2: Total Smart Metering Revenue ($m), Split by 8 Key Regions,

2022-2027. 17

Contents