Product Code: 62367
The smart grid data analytics market is expected to grow at a CAGR of 25%, during the forecast period 2019 - 2024. With the increase of Internet of Things (IoT) and big data analytics coupled with rapidly growing penetration of information and communication technologies (ICT) in the grid, modernization has led to the emergence of smart grid data analytics.
- The primary consumers for smart grid data analytics solutions are the utility service providers. These solutions are set up at the end of utility providers in order to help taking better decisions for optimizing the grid operations. Therefore, this is expected to substantially spur the smart grid data analytics market growth.
- Additionally, the smart grids play nowadays a major role in the integration of the smart cities concept by putting into effect the smart energy conceptual element i.e. smart electrical energy systems that interconnect utilities and end-users by means of smart infrastructure. Thus, the demand for cost-effective and sustainable power supplies has led the market for smart grid analytics.
- However, the high cost of the initial investment in the smart grids system is acting a hindrance to this market during the forecast period.
Scope of the Report
Big data analytics combined with grid visualization can lead to better situational awareness and predictive decisions. Predictive maintenance and fault detection based on data analytics with advanced metering infrastructure is more crucial to the security of the power system. Moreover, at the end-user level, smart grids can enable demand flexibility and consumer participation in the energy system, including through demand response, electric vehicle (EV) charging and self-produced distributed generation and storage. Thus, lots of data will be generated in terms of usage and it has catalyzed the smart grid data analytics market.
Key Market Trends
Increasing Investment in the Smart Grid Infrastructure Offers Potential Growth
- Smart grids represent a new era in the electrical sector, as they go from static one-way management to dynamic two-way management. In this, users are informed of their real consumption and thus the contracted power can be adjusted to meet the real need of each consumer. This increases efficiency and energy savings.
- Further, smart grids collect much more data than the manual energy meter reading system. This permits the use of data analysis techniques and the preparation of highly realistic consumption forecasts as many more variables are taken into account. Therefore, the opportunities for smart grid analytics are expanding because there's exponentially more data available to develop analytical models.
- Additionally, the smart grid optimizes asset utilization and operates efficiently which means desired functionality at minimum cost. Nowadays, many companies have been modernizing power plants and substations by putting sensors on the main components, such as turbines and transformers which look for vibration or other anomalies that could predict future failures. Thus, those companies apply smart grid analytics to optimize the performance of connected devices in the field. For instance, Duke Energy claims that these smart grid data analytics have already paid off in big ways by preventing major outages related to equipment.
- Therefore, the analysis obtained from smart grid data analytics offers a significant advantage in terms of cost reduction, personalized energy services to consumers, etc. This in return creates a positive outlook for the market during the forecast period.
Asia-Pacific to Witness the Fastest Growth
- The Asia-Pacific region is being dominated by two highly populated country i.e. India and China. The rising population in countries like China, Japan, and India has stimulated the demand for residential infrastructure and electricity consumption, therefore accelerating the demand for electricity in the nations mentioned above is the crucial attribute backing the demand of smart grids which in return will create a market for smart grid data analytics as well because of the benefits associated with it.
- Moreover, according to NITI Aayog, India is home to 18% of the world's population but uses only 6% of the world's primary energy. India's energy consumption has almost doubled since 2000 and the potential for further rapid growth is enormous. Urbanization coupled with smart city initiatives will be a key diver of this trend which in result will create a positive outlook for the smart grid data analytics market whose main aim is to optimize their efficiency and minimize losses occurring in electricity generation and distribution of power supply.
- Therefore, all the above factors combined will fuel the smart grid market which in return will boost the smart grid data analytics market in the Asia-Pacific region during the forecasted period.
The smart grid data analytics market is fragmented and highly competitive in nature. Due to its anticipated high growth in the coming years, many more companies are expected to enter the market in the near future. Currently, the majority of the software vendors are turning towards partnerships and joint ventures with different players operating in the relative markets. Some of the key players are Siemens AG, IBM Corporation, SAP SE, Infosys Limited, Accenture amongst others. Few recent developments in this market are:
- May 2018 - Itron, Inc. signed a contract with Jamaica Public Service Company (JPS) for a nationwide smart grid deployment, serving more than 600,000 customers, that helped the utility to improve customer service, drive grid reliability and enable revenue realization.
Reasons to Purchase this report:
- The market estimate (ME) sheet in Excel format
- Report customization as per the client's requirements
- 3 months of analyst support
Table of Contents
- 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 Growing Demand for Power Supplemented by Higher Transmission and Distribution Losses
- 4.3.2 Growing Investment in the Smart Grid Systems
- 4.4 Market Restraints
- 4.4.1 High Costs of Smart Grid Systems
- 4.5 Industry Value Chain Analysis
- 4.6 Industry Attractiveness - Porter's Five Force Analysis
- 4.6.1 Threat of New Entrants
- 4.6.2 Bargaining Power of Buyers/Consumers
- 4.6.3 Bargaining Power of Suppliers
- 4.6.4 Threat of Substitute Products
- 4.6.5 Intensity of Competitive Rivalry
5 MARKET SEGMENTATION
- 5.1 By Deployment
- 5.1.1 Cloud-Based
- 5.1.2 On-premises
- 5.2 By Solution
- 5.2.1 Advanced Metering Infrastructure Analytics
- 5.2.2 Demand Response Analytics
- 5.2.3 Grid Optimisation Analytics
- 5.3 By End-user Vertical
- 5.3.1 Small & Medium Enterprises
- 5.3.2 Large Enterprises
- 5.3.3 Public Sector
- 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 and Africa
6 COMPETITIVE LANDSCAPE
- 6.1 Company Profiles
- 6.1.1 Siemens AG
- 6.1.2 Itron
- 6.1.3 AutoGrid Systems, Inc.
- 6.1.4 AutoGrid Systems, Inc.
- 6.1.5 Verizon
- 6.1.6 IBM Corporation
- 6.1.7 SAP SE
- 6.1.8 HP Development Company, LP
- 6.1.9 HP Development Company LP
- 6.1.10 SAS Institute Inc.
- 6.1.11 Hitachi Consulting Corporation
- 6.1.12 Dell EMC
- 6.1.13 Infosys Limited
- 6.1.14 Accenture PLC
- 6.1.15 Capgemini SE
- 6.1.16 Oracle Corporation
- 6.1.17 Amdocs Corporation
- 6.1.18 Sensus
7 INVESTMENT ANALYSIS
8 MARKET OPPORTUNITIES AND FUTURE TRENDS