27-Dec-2022 | Zion Market Research
The global smart grid analytics market size was worth around USD 2.75 billion in 2021 and is predicted to grow to around USD 5.92 billion by 2030 with a compound annual growth rate (CAGR) of roughly 11.81% between 2022 and 2030.
A smart grid is defined as a set of advanced technology and tools in an electrical network for monitoring and managing the supply of electricity from various sources to meet different consumer demands. Smart grid analytics is the analysis of information collected allowing businesses to make useful and future-oriented decisions and stay ready for many changes in the demand or supply of electricity.
Smart grids have become essential in today’s modern world as they allow coordination and the ability to supply electricity from all grid operators, generators, users, and market stakeholders resulting in optimum operation of all parts in the system thus improving energy efficiency. With the growing population, industrialization, and practically the entire world running on a constant supply of electricity, the world has reached a stage where smart and data-backed decisions are the only way forward for sustainable growth.
Smart grid analytics are important because they can mine the immense data collected by smart grids and convert them into meaningful information. Some of the related data are weather factors and real-time asset metrics which when applied to analytics, performance of the connected devices can be optimized. It is beneficial for the economic growth of businesses as well since it can help control operational expenses while delivering customized energy solutions to consumers and offering upgraded grid reliability.
The global smart grid analytics market is projected to grow owing to the high demand for an equal and constant supply of energy across regions including urban and rural areas in under-developed economies. Growing emphasis on renewable sources of energy may also help higher adoption of smart grids and related systems like analytics due to consumer awareness and initiatives undertaken by government and responsible authorities to promote the use of green or clean energy.
Non-renewable sources for energy generation are not sustainable and leave a harmful impact on the environment leading to more end-consumers and businesses preferring eco-friendly sources of energy. The global market may also benefit from the rising awareness about the internet of things (IoT) and interest in big data analytics. Most of the world’s leading companies have invested in big data analytics and businesses operating in smart grids are now entering the list due to the benefits associated with the technology.
However, many authorities have shown significant concerns over health and fire risks associated with smart grids which could impact the adoption of analytics in the global market. Security and privacy concerns may also impact the growth trend as any technology is prone to cyber-attacks.
Modernization is expected to act as a positive influence for further growth while the high reliability of skilled labor may create challenging scenarios for businesses.
The global smart grid analytics market is segmented based on deployment model, component, type, end-user, and region.
Based on components, the global market is divided into services, solutions, managed, and professional with services leading the global market segment in 2021 followed by solutions. Many businesses in the smart grid sector have outsourced their analytics system to other companies owing to the expertise offered by the external agency. Companies like Accenture and Capgemini only work on outsourced projects. Although it is an added cost, the overall service offered contributes to higher revenue thus absorbing the expense of outsourcing analytics work. In 2021, Capgemini broke all records when it amassed a revenue of INR 18,160 million.
Based on end-user, the global market segments are public sector, large enterprises, and small & medium size firms. As of 2021, the public sector was the largest consumer of smart grid analytics marginally followed by large enterprises. Since the cost of installation of such technologies is extremely high, currently only public sector firms and private organizations with large capital can easily invest in these systems. The US government passed the American Recovery and Reinvestment Act in 2009 setting apart over USD 4.5 billion for the installation of smart grids in the country.
North America dominated the global smart grid analytics market in 2021 and is anticipated to continue the trend during the projection period. The changing political situations across the globe are expected to push the US government and private companies to upgrade their systems and power generation and management capacity as Russia and the US political dynamic change. Asia-Pacific is a lucrative market for global market players as investments in infrastructure development including the energy sector increases with India, China, and Japan leading the regional growth.
The growing interest of foreign companies in the Indian market will allow for higher installations in the country as the demand for energy supply grows along with the population and industrialization. The country is one of the top-ranking economies in terms of information technology services thus adding to the country’s contribution to regional revenue.
This review is based on a report by Zion Market Research, titled “Smart Grid Analytics Market By Deployment Model (Cloud-Based, On-Premise, and Hybrid), By Component (Services, Solution, Managed, and Professional), By Type (Generalized Solutions, and Specialized Solutions), By End-User (Public Sector, Large Enterprises, and Small & Medium Size Enterprises), and By Region - Global and Regional Industry Overview, Market Intelligence, Comprehensive Analysis, Historical Data, and Forecasts 2022 – 2030.”- Report at https://www.zionmarketresearch.com/report/smart-grid-analytics-market
Recent Developments:
The global smart grid analytics market is home to players including:
The global smart grid analytics market is segmented as follows:
By Deployment Model
By Component
By Type
By End-User
By Region
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