Technology

Global Next-Generation Smart Grid Solutions Market was valued at $ 11.6 Billion in 2023 and is projected to grow at a CAGR of 22.4% through 2030

Published

2 years ago

February 26, 2024

MILWAUKEE, Feb. 26, 2024 /PRNewswire/ — The “Global Next-Generation Smart Grid Solutions Market by Component (Hardware, Software, Services), by Technology (Advanced Metering Infrastructure (AMI), Grid Automation, Communication Networks, Renewable Energy Integration (Distributed Energy Resources (DERs), Microgrids, Energy Storage), Big Data Analytics, Cybersecurity, Artificial Intelligence (AI) and Machine Learning, and Others), by Application (Generation, Transmission, Distribution, Consumption), by End User (Utilities, Industrial, Commercial, Residential), and by Regions-Forecast to 2030” report has been added to Tersus Strategy’s offering.

The next-generation smart grid solutions market is experiencing significant growth and innovation as utilities worldwide seek to modernize and enhance the efficiency of their power distribution systems. This market is characterized by the integration of advanced technologies such as smart meters, grid automation, communication networks, and artificial intelligence. Key drivers for the adoption of these solutions include the need for improved grid reliability, integration of renewable energy sources, and the rising demand for energy efficiency.

Major players in the market, including General Electric (GE), Siemens, ABB, and Schneider Electric, are at the forefront of providing comprehensive smart grid solutions. These solutions encompass intelligent substations, distribution automation, cybersecurity measures, and advanced metering infrastructure. As the world transitions towards a more sustainable energy future, the market also sees the integration of renewable energy sources, demand response programs, and electrification of transportation into the smart grid ecosystem.

The convergence of big data analytics, artificial intelligence, and IoT technologies is empowering utilities to make data-driven decisions, optimize grid operations, and enhance predictive maintenance. Cybersecurity remains a critical focus to protect smart grid infrastructure from potential threats. The market is witnessing standardization efforts to ensure interoperability among diverse components and systems. Overall, the next-generation smart grid solutions market is poised for continued expansion, driven by the ongoing global energy transition and the need for resilient, sustainable, and intelligent power distribution systems.

For more information about this report visit: https://tersusstrategy.com/product/global-next-generation-smart-grid-solutions-market-2024-2030/

In the dynamic landscape of next-generation smart grid solutions, various trends shape different facets of the energy ecosystem. In power generation, the integration of distributed energy resources (DERs) and renewable sources is a prominent trend, fostering cleaner and more sustainable energy production. Transmission networks are witnessing advancements in digital substations and grid automation, enhancing reliability and adaptability to changing grid conditions. Distribution systems are undergoing a transformation with the introduction of distribution automation and self-healing grids, optimizing efficiency and minimizing downtime. At the consumption level, smart grid technologies empower consumers through real-time data, enabling better energy management and the integration of demand-side management. The rise of smart home technologies and dynamic pricing models further engages consumers in efficient energy usage. Overall, the smart grid landscape is characterized by trends that collectively drive towards a more resilient, sustainable, and interactive energy ecosystem across the entire energy value chain

Across diverse end-user segments, the trends in next-generation smart grid solutions reflect the evolving needs and priorities of utilities, industrial entities, commercial enterprises, and residential consumers. For utilities, a trend involves extensive grid modernization efforts, including the integration of advanced analytics and artificial intelligence for predictive maintenance and optimal grid operations. In the industrial sector, the adoption of smart grid technologies is characterized by enhanced energy efficiency measures, demand response systems, and the integration of renewable energy sources into manufacturing processes. Commercial entities are increasingly leveraging smart grid solutions to optimize energy consumption through building management systems, IoT-driven sensors, and data analytics, resulting in operational cost savings. In residential settings, the proliferation of smart meters, home energy management systems, and the growing use of electric vehicles contribute to a more informed and engaged consumer base, promoting energy conservation and sustainability. These trends collectively underscore the broad and transformative impact of smart grid technologies across diverse end-user segments.

Request detailed sample of this study: https://tersusstrategy.com/product/global-next-generation-smart-grid-solutions-market-2024-2030/

Key Topics Covered:

1. Report Scope

1.1. Market Segmentation and scope

1.2. Regional Scope

1.3. Estimates and forecast timeline

2. Market Research Methodology

2.1. Research methodology and design

2.2. Sample selection

2.3. Reliability and validity

3. Executive Summary

4. Market Analysis

4.1. Market size and growth rates

4.2. Market growth drivers, market dynamics and trends

4.3. Market scenarios and opportunity forecasts

4.4. Market constraints and challenges

4.5. Industry value chain analysis

4.6. Industry analysis – Porter’s

4.6.1. Threat of new entrants

4.6.2. Bargaining power of suppliers

4.6.3. Bargaining power of buyers

4.6.4. Threat of substitutes

4.6.5. Competitive rivalry

4.7. PEST analysis

4.7.1. Political/legal landscape

4.7.2. Economic landscape

4.7.3. Social landscape

4.7.4. Technological landscape

5. Market Breakdown by Component

5.1. Introduction

5.2. Hardware

5.2.1. Smart Meters

5.2.2. Sensors

5.2.3. Communication Infrastructure

5.2.4. Transformers

5.2.5. Others

5.3. Software

5.3.1. Grid Management Systems

5.3.2. Asset Management Systems

5.3.3. Data Analytics and AI/ML Platforms

5.3.4. Security and Cybersecurity Solutions

5.3.5. Customer Engagement and Billing Systems

5.4. Services

5.4.1. Consulting

5.4.2. Deployment and Integration

5.4.3. Support and Maintenance

5.4.4. Training and Education

6. Market Breakdown by Technology

6.1. Introduction

6.2. Advanced Metering Infrastructure (AMI)

6.3. Grid Automation

6.4. Communication Networks

6.5. Renewable Energy Integration

6.5.1. Distributed Energy Resources (DERs)

6.5.2. Microgrids

6.5.3. Energy Storage

6.6. Big Data Analytics

6.7. Cybersecurity

6.8. Artificial Intelligence (AI) and Machine Learning

6.9. Others

7. Market Breakdown by Application

7.1. Introduction

7.2. Generation

7.3. Transmission

7.4. Distribution

7.5. Consumption

8. Market Breakdown by End User

8.1. Introduction

8.2. Utilities

8.3. Industrial

8.4. Commercial

8.5. Residential

9. Market Breakdown – by Geography

9.1. North America

9.1.1. North America Next-Generation Smart Grid Solutions Market, 2024-2030

9.1.2. North America Next-Generation Smart Grid Solutions Market, by Component

9.1.3. North America Next-Generation Smart Grid Solutions Market, by Technology

9.1.4. North America Next-Generation Smart Grid Solutions Market, by Application

9.1.5. North America Next-Generation Smart Grid Solutions Market, by End User

9.1.6. North America Next-Generation Smart Grid Solutions Market, by Country

9.1.6.1. U.S.

9.1.6.2. Canada

9.1.6.3. Mexico

9.2. South America

9.2.1. South America Next-Generation Smart Grid Solutions Market, 2024-2030

9.2.2. South America Next-Generation Smart Grid Solutions Market, by Component

9.2.3. South America Next-Generation Smart Grid Solutions Market, by Technology

9.2.4. South America Next-Generation Smart Grid Solutions Market, by Application

9.2.5. South America Next-Generation Smart Grid Solutions Market, by End User

9.2.6. South America Next-Generation Smart Grid Solutions Market, by Country

9.2.6.1. Argentina

9.2.6.2. Brazil

9.2.6.3. Others

9.3. Europe

9.3.1. Europe Next-Generation Smart Grid Solutions Market, 2024-2030

9.3.2. Europe Next-Generation Smart Grid Solutions Market, by Component

9.3.3. Europe Next-Generation Smart Grid Solutions Market, by Technology

9.3.4. Europe Next-Generation Smart Grid Solutions Market, by Application

9.3.5. Europe Next-Generation Smart Grid Solutions Market, by End User

9.3.6. Europe Next-Generation Smart Grid Solutions Market, by Country

9.3.6.1. Germany

9.3.6.2. France

9.3.6.3. U.K.

9.3.6.4. Russia

9.3.6.5. Italy

9.3.6.6. Spain

9.3.6.7. Sweden

9.3.6.8. Switzerland

9.3.6.9. Finland

9.3.6.10. Ireland

9.3.6.11. Poland

9.3.6.12. Austria

9.3.6.13. Norway

9.3.6.14. Netherlands

9.3.6.15. Others

9.4. Asia-Pacific

9.4.1. APAC Next-Generation Smart Grid Solutions Market, 2024-2030

9.4.2. APAC Next-Generation Smart Grid Solutions Market, by Component

9.4.3. APAC Next-Generation Smart Grid Solutions Market, by Technology

9.4.4. APAC Next-Generation Smart Grid Solutions Market, by Application

9.4.5. APAC Next-Generation Smart Grid Solutions Market, by End User

9.4.6. APAC Next-Generation Smart Grid Solutions Market, by Country

9.4.6.1. China

9.4.6.2. Japan

9.4.6.3. South Korea

9.4.6.4. India

9.4.6.5. Singapore

9.4.6.6. Australia

9.4.6.7. Others

9.5. Middle East & Africa

9.5.1. MEA Next-Generation Smart Grid Solutions Market, 2024-2030

9.5.2. MEA Next-Generation Smart Grid Solutions Market, by Component

9.5.3. MEA Next-Generation Smart Grid Solutions Market, by Technology

9.5.4. MEA Next-Generation Smart Grid Solutions Market, by Application

9.5.5. MEA Next-Generation Smart Grid Solutions Market, by End User

9.5.6. MEA Next-Generation Smart Grid Solutions Market, by Country

9.5.6.1. Saudi Arabia

9.5.6.2. UAE

9.5.6.3. Israel

9.5.6.4. Qatar

9.5.6.5. South Africa

9.5.6.6. Others

10. Competitive Landscape

10.1. Company Market Positioning

10.2. Company Geographical Presence Analysis

10.3. Market Revenue Share Analysis (%), by Leading Players

11. Company Profiles

• Company Overview

• Financial Performance

• Product Benchmarking

• Recent Developments

Established Players

1. General Electric

2. Siemens

3. Schneider Electric

4. ABB

5. Eaton

6. Itron

7. Landis+Gyr

8. EDMI

9. Enel

10. Engie

11. Iberdrola

12. Honeywell

13. Cisco

14. Huawei

15. Microsoft

16. IBM

17. Oracle

Emerging Players

18. GridBeyond

19. sonnen GmbH

20. AutoGrid

21. Greenbird Integration Technology

22. Enchanted Rock

23. Guardtime

For more information about this report visit : https://tersusstrategy.com/product/global-next-generation-smart-grid-solutions-market-2024-2030/

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Tersus Strategy
Kevin Matthew, Business Development Manager
Info@tersusstrategy.com
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Technology

Zifo Transforms Ontology Engineering with AI-Powered Intelligent Automation

Published

4 hours ago

April 30, 2026

Advanced AI solution speeds up ontology creation by 80%, generating structured, interoperable knowledge models for science-driven organizations.

CAMBRIDGE, Mass. and CAMBRIDGE, England, April 30, 2026 /PRNewswire/ — Zifo, the leading global enabler of AI and data-driven enterprise informatics for science-driven organizations, has developed an Intelligent Automation solution for Ontology Engineering, which is designed to seamlessly generate structured, interoperable knowledge models while accelerating ontology creation by 80%.

Overcoming the Bottlenecks of Manual Ontology Creation

Manual ontology creation in the biopharma industry has traditionally been a time-consuming process that requires specialized expertise. Organizations frequently struggle with semantic ambiguity, complex integration challenges, and limited scalability, resulting in workflows that can take weeks to complete. Zifo’s AI-powered automation tackles these challenges head-on by eliminating 80% of the manual work through automated class generation, description creation, and precise IRI mapping.

Addressing the Complexities of Semantic Knowledge

Developing comprehensive knowledge models often demands deep domain expertise to define relationships and align terminology. Zifo’s intelligent solution overcomes this by providing an AI-guided workflow featuring an intuitive interface, meaning specialized ontology engineering knowledge is no longer required. By leveraging LLM-powered generation, the solution creates precise definitions with a deep understanding of domain-specific context, while generating standardized synonyms and establishing controlled vocabulary alignment to eliminate inconsistent terminology.

A Solution Designed for Scalable Scientific Data Modeling

The AI-powered solution addresses critical format compatibility and integration points in ontology management:

Seamless Integration: Automated mapping connects directly to established ontologies, including NCIT, CHEBI, OBI, and EFO, via BioPortal and OLS APIs.Massive Scalability: Parallel processing and batch operations empower teams to execute large-scale ontology projects without performance limitations.Automated Hierarchies: The AI autonomously generates semantic relationships and parent-child hierarchies based on domain context and predefined relation vocabularies.Format Compatibility: The solution produces direct OWL/RDF exports with proper URIs, ensuring seamless downstream integration.

Unique Features include:

Multi-Source Integration: The solution combines BioPortal, OLS, and EMBL-EBI APIs to guarantee comprehensive ontology coverage.Intelligent Ranking System: The system uses AI-powered relevance scoring and justification for precise ontology mappings.Precise IRI Mapping: It ensures that each generated class is linked to the correct IRI, directly promoting semantic web compatibility.Human-in-the-Loop Design: The solution automates repetitive tasks while maintaining vital expert oversight.End-to-End Workflow: Users are guided through a complete pipeline, from initial domain knowledge input straight to exportable OWL files.Visual Knowledge Graph: An interactive graph visualization allows for intuitive relationship exploration and validation.Multi-Format Exports: Provides seamless export options in CSV, OWL, or HTML Ontograph formats for downstream use, collaboration, and visualization.

Strategic Value Across the Scientific Chain

This solution breaks down the traditional barriers of data structuring. Built on a robust backend of Python, LangChain, and leading LLM models, alongside a frontend framework using Next.js 15 and Cytoscape.js for graph visualization, the solution is highly adaptable. Furthermore, future optimization enhancements will include provisions for uploading user-defined classes or semi-ready ontologies.

About Zifo

Zifo is the leading global enabler of AI and data-driven enterprise informatics for science-driven organizations. With expertise spanning research, development, manufacturing, and clinical domains, Zifo serves a diverse range of industries including Pharma, Biotech, Chemicals, Food and Beverage, and more. Trusted by over 190 organizations worldwide, Zifo is the partner of choice for advancing digital scientific innovation.

For more information, visit www.zifornd.com; https://zifornd.com/practical-ai-blueprints/

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SOURCE Zifo Technologies

Technology

UNC-Chapel Hill establishes ‘Carolina in the Capital’ with new Washington, D.C. office

Published

4 hours ago

April 30, 2026

CHAPEL HILL, N.C., April 30, 2026 /PRNewswire/ — The University of North Carolina at Chapel Hill has opened a new office in Washington, D.C., establishing an expanded presence for the University in the nation’s capital and creating exciting opportunities for students, faculty, staff and alumni.

Located at 101 Constitution Avenue NW, the 10,861-square-foot space – coined “Carolina in the Capital” – will support a variety of functions, including educational programming for undergraduate and graduate students, alumni relations and engagement with government partners.

As a leading R1 university, UNC-Chapel Hill annually attracts more than $1.6 billion to the state’s economy to fund research that creates a better quality of life for all its citizens. More than 60% of UNC-Chapel Hill’s total research funding comes from federal sponsors with the majority of that federal funding coming from the National Institutes of Health (NIH), which is based in the Washington area.

“Carolina in the Capital is a state-of-the-art facility that reflects our commitment to creating experiential learning opportunities for our students and faculty,” said Chancellor Lee H. Roberts. “The space is designed as an immersive learning environment where students can translate classroom knowledge into hands-on experience, which has never been more important. The facility also strengthens our ability to support engagement between our staff, alumni, policymakers and partners.”

Supporting students participating in Carolina’s Washington-based academic programs is a priority. For years, students and faculty have relied on temporary or borrowed spaces across the city. The new office provides a permanent home where students can gather, learn and build community while living and studying in Washington. A robust schedule of classes and events will fill the space throughout the year.

The Washington, D.C. region is home to the largest concentration of out-of-state Carolina alumni anywhere in the country. The new office creates a dedicated space to strengthen those connections and support networking, mentorship, professional development and community-building among D.C.-based Tar Heels.

The space will also serve as a platform to bring Carolina’s research and academic expertise into closer conversation with policymakers, industry leaders and member organizations. Carolina is the nation’s 11th largest university in the country based on research volume with primary federal funding coming from NIH and the National Science Foundation (NSF), both based in the D.C. area. Carolina is a proud member of the Association of American Universities (AAU) and the Association of Public & Land Grant Universities (APLU), which are both based in Washington.

The office is funded entirely through the UNC-Chapel Hill Foundation and does not use any state appropriations.

You can view additional photos of the space here.

Media Contact: UNC Media Relations, 919-445-8555, mediarelations@unc.edu

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SOURCE University of North Carolina at Chapel Hill Office of Communications

Technology

Investing.com Acquires Stonki to Accelerate Its Entry into the Agentic AI Era

Published

4 hours ago

April 30, 2026

The acquisition strengthens Investing.com’s AI capabilities, advancing a next-generation research assistant that can analyze markets, generate insights, and guide investors in real time

NEW YORK, April 30, 2026 /PRNewswire/ — Investing.com, one of the world’s largest financial platforms used by more than 60 million investors each month, today announced the acquisition of Stonki, an AI-powered investing assistant designed to help traders turn ideas into structured, actionable trading plans.

The move marks a major step in the company’s evolution toward agentic AI, strengthening its ability to deliver faster, deeper, and more actionable market insights to a growing base of more than 300,000 paying subscribers across its InvestingPro suite, the company’s premium subscription offering for advanced market data, tools, and AI-driven insights.

Over the past 12 months, nearly 3 million users have used WarrenAI, Investing.com’s AI-powered financial research assistant launched last year, to perform market analysis, making AI a central entry point into the platform’s ecosystem. With the addition of Stonki, the company is moving beyond traditional AI tools toward agentic systems that can proactively guide users through the investment process.

“We’re entering the age of agentic AI, where the technology moves beyond just answering questions to actively helping investors think, analyze, and act,” said Omer Shvili, CEO of Investing.com. “Bringing Stonki.ai into the fold accelerates our goal of building an agentic platform that will serve as a 24/7 analyst for our users. We are developing this to be more than just a tool; it will be a partner that identifies opportunities, tracks unfolding situations, and surfaces trade ideas even when the user isn’t active—giving our users the kind of edge that was previously only available to professional investors.”

Founded in 2025, Stonki is developing a new category of ‘agentic’ AI for investing, enabling users to turn investment ideas into fully defined strategies with entry and exit conditions, risk management rules, and continuous monitoring.

“We started Stonki because, as investors and traders ourselves, we knew how much time and focus it takes to stay on top of the market and properly manage a day trade, a swing trade, an investment idea, or a portfolio,” said Ulas Bilgenoglu and Itay Verkh, co-founders of Stonki. “We set out to build AI that could carry part of that load by continuously monitoring the market, turning ideas into structured strategies, and helping users make better decisions with clear entry and exit conditions, disciplined risk management, and ongoing tracking. Joining Investing.com gives us the scale, data, reach, and strong AI foundation to accelerate that vision. Together, we can create an experience where AI helps users stay ahead of the market, manage risk, and act with greater confidence.”

The acquisition expands Investing.com’s AI capabilities across both technical and fundamental investing workflows. Stonki’s technology is built around persistent, real-time intelligence, continuously monitoring markets, tracking user-defined strategies, and alerting investors when conditions align, rather than relying on one-off prompts or static analysis.

For active traders, the platform is evolving into a real-time analysis engine designed to support high-frequency decision-making with precision and speed. For long-term investors, it is becoming a central hub for research, enabling users to evaluate opportunities, set personalized alerts, and monitor portfolios based on their individual investment strategies.

Users will be able to define specific conditions, such as a stock crossing a long-term moving average, and have the AI continuously monitor the market, analyze relevant signals, and surface actionable insights in real time. The system will also review portfolios on an ongoing basis, helping investors avoid potential losses and uncover new opportunities aligned with their strategy.

This latest step builds on Investing.com’s broader strategy of expanding its AI-powered suite, including WarrenAI, ProPicks AI, and its recently launched AI Chart Analysis, all aimed at delivering faster, more accurate and more actionable insights to investors.

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SOURCE Investing.com