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Global Smart Grid Network Market to reach USD XXX billion by the end of 2030

Global Smart Grid Network Market Size study & Forecast, by Technology Application Area (Transmission, Demand Response, Advanced Metering Infrastructure (AMI), Other Technology Application Areas) and Regional Analysis, 2023-2030

Product Code: EPPGS-63999130
Publish Date: 20-10-2023
Page: 200

Global Smart Grid Network Market is valued approximately USD XX billion in 2022 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2023-2030. A Smart Grid Network is an advanced electrical power distribution system that uses digital communication and information technology to optimize the generation, transmission, and consumption of electricity. It is an upgraded version of the traditional power grid that incorporates two-way communication between various components, such as power plants, substations, electrical devices, and consumers. The primary goal of a Smart Grid Network is to enhance the efficiency, reliability, sustainability, and flexibility of the electricity supply. It achieves this by enabling real-time monitoring, control, and management of the power grid, allowing for better integration of renewable energy sources, efficient demand response programs, and improved outage detection and restoration. The Smart Grid Network market is expanding because of factors such as rising investment and deployment of smart grid technologies and the rise in the adoption of electric vehicles across the globe.

Increased investment and deployment of smart grid technologies such as smart meters, and advanced metering infrastructure is driving the market growth. For instance, The Australian Energy Market Commission announced plans to install electricity meters in the nation in December 2020 and started an independent assessment of the regulations controlling electricity meters to find new ways to accelerate the deployment. Similarly to this, the Indian government stated in February 2020 that the Smart Meter National Programme (SMNP) would install 1 million smart meters across the nation. Further, in May 2020, The U.K. government’s program for implementing smart meters resulted in the installation of 26.6 million electricity meters across domestic buildings in Great Britain as of May 2020. These meters are managed by major energy companies. Thus, the rising deployment of smart grid technologies is driving market growth. In addition, rising smart city projects, grid modernization and government investment in adoption of smart grid networks are some factors creating a lucrative opportunity to market growth. However, the high cost of smart grid networks stifles market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Smart Grid Network Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to factors such as rising investment in smart grid projects, the number of smart city projects, the presence of key market players, and rising technological advancement in grid technologies. Whereas, Asia Pacific is projected to register the fastest growth owing to factors such as rising adoption of electric vehicles, rising number of smart cities projects, and rising investment in smart grid technologies in the region.

Major market player included in this report are:
ABB Ltd
Cisco Systems Inc.
Eaton Corporation PLC
General Electric Company
Itron Inc.
Osaki Electric Co. Ltd
Hitachi Ltd
Schneider Electric SE
Siemens AG
Honeywell International Inc.

Recent Developments in the Market:
Ø In January 2021, Schneider Electric acquired DC Solutions BV, a prominent supplier of smart solutions. As a result, through this acquisition Schneider Electric has made strides in the electrical distribution and smart grid industries.

Global Smart Grid Network Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Technology Application Area, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and Technology Application Area offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Technology Application Area:
Transmission
Demand Response
Advanced Metering Infrastructure (AMI)
Other Technology Application Areas

By Region:

North America
U.S.
Canada

Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC

Latin America
Brazil
Mexico

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Smart Grid Network Market, by Region, 2020-2030 (USD Billion)
1.2.2. Smart Grid Network Market, by Technology Application Area, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Smart Grid Network Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Smart Grid Network Market Dynamics
3.1. Smart Grid Network Market Impact Analysis (2020-2030)
3.1.1. Market Drivers
3.1.1.1. Rising investment and deployment of smart grid technologies
3.1.1.2. Rising adoption of electric vehicles
3.1.2. Market Challenges
3.1.2.1. High Cost of Smart Grid Network
3.1.3. Market Opportunities
3.1.3.1. Rising smart cities projects
3.1.3.2. Grid modernization
3.1.3.3. Rising government investment for adoption of smart grid network
Chapter 4. Global Smart Grid Network Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Smart Grid Network Market, by Technology Application Area
5.1. Market Snapshot
5.2. Global Smart Grid Network Market by Technology Application Area, Performance – Potential Analysis
5.3. Global Smart Grid Network Market Estimates & Forecasts by Technology Application Area 2020-2030 (USD Billion)
5.4. Smart Grid Network Market, Sub Segment Analysis
5.4.1. Transmission
5.4.2. Demand Response
5.4.3. Advanced Metering Infrastructure (AMI)
5.4.4. Other Technology Application Areas
Chapter 6. Global Smart Grid Network Market, Regional Analysis
6.1. Top Leading Countries
6.2. Top Emerging Countries
6.3. Smart Grid Network Market, Regional Market Snapshot
6.4. North America Smart Grid Network Market
6.4.1. U.S. Smart Grid Network Market
6.4.1.1. Technology Application Area breakdown estimates & forecasts, 2020-2030
6.4.2. Canada Smart Grid Network Market
6.5. Europe Smart Grid Network Market Snapshot
6.5.1. U.K. Smart Grid Network Market
6.5.2. Germany Smart Grid Network Market
6.5.3. France Smart Grid Network Market
6.5.4. Spain Smart Grid Network Market
6.5.5. Italy Smart Grid Network Market
6.5.6. Rest of Europe Smart Grid Network Market
6.6. Asia-Pacific Smart Grid Network Market Snapshot
6.6.1. China Smart Grid Network Market
6.6.2. India Smart Grid Network Market
6.6.3. Japan Smart Grid Network Market
6.6.4. Australia Smart Grid Network Market
6.6.5. South Korea Smart Grid Network Market
6.6.6. Rest of Asia Pacific Smart Grid Network Market
6.7. Latin America Smart Grid Network Market Snapshot
6.7.1. Brazil Smart Grid Network Market
6.7.2. Mexico Smart Grid Network Market
6.8. Middle East & Africa Smart Grid Network Market
6.8.1. Saudi Arabia Smart Grid Network Market
6.8.2. South Africa Smart Grid Network Market
6.8.3. Rest of Middle East & Africa Smart Grid Network Market

Chapter 7. Competitive Intelligence
7.1. Key Company SWOT Analysis
7.1.1. Company 1
7.1.2. Company 2
7.1.3. Company 3
7.2. Top Market Strategies
7.3. Company Profiles
7.3.1. ABB Ltd
7.3.1.1. Key Information
7.3.1.2. Overview
7.3.1.3. Financial (Subject to Data Availability)
7.3.1.4. Product Summary
7.3.1.5. Recent Developments
7.3.2. Cisco Systems Inc.
7.3.3. Eaton Corporation PLC
7.3.4. General Electric Company
7.3.5. Itron Inc.
7.3.6. Osaki Electric Co. Ltd
7.3.7. Hitachi Ltd
7.3.8. Schneider Electric SE
7.3.9. Siemens AG
7.3.10. Honeywell International Inc.
Chapter 8. Research Process
8.1. Research Process
8.1.1. Data Mining
8.1.2. Analysis
8.1.3. Market Estimation
8.1.4. Validation
8.1.5. Publishing
8.2. Research Attributes
8.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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