Smart Grid Data Analytics Market - Global Industry Trend Analysis 2012 to 2017 and Forecast 2017 - 2025


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Global Smart Grid Data Analytics Market: Introduction

Smart grid is a new technology that helps the system to run effectively and smart grid data analytics provide the optimized solution to the complete system. Increasing demand for the cost-effective power supply from the consumer end and minimization of production of electricity cost by using the smart grid data analytics owing to its properties drives the growth of the market. To optimize the system and by replacing aged system with the smart meters, sensors, and automation of complete system help the utility owners to operate the complete network efficiently. The data generated by the all the smart meter, sensors and other automated systems are collected and analysed in huge volume, this data can be analysed and estimated from the production and supply. For the effective operation of power system the smart grid data helps the utility service providers to analyse the power demand from consumers end.

Smart grid data analytics helps to collect valuable information generated by all the equipment. It helps to analyse the data and predict the load for future, such as forecasting for short-term, medium-term, and long-term can be achieved. Load forecasting is prediction of future load by taking the previous data which is available. Load forecasting is important in power systems, it helps in operations, as power generated by the generating stations should be equal to the demand from the consumer end and any excessive power generation may turn to huge loss for the utility network. Another use of smart grid data analytics is identifying the behaviour of load flow. By using the analytics we are able to find out the solutions for the system in an improved manner. Grid is nothing but interconnection of complete power system right from generating station to transmission to substation to local substation to the consumer. Using the smart grid data analytics we are able to identify the peak load and the dip, complete load behaviour. By analysing the load behaviour we are able to reduce the power cuts, which helps the transmission sector, especially the load dispatching centres.

Global Smart Grid Data Analytics Market: Segmentation

The global smart grid data analytics market is segmented as follows:

By solution type, the market is segmented into:

  • Ami analytics
  • Demand response
  • Grid optimization
  • Asset management
  • Energy forecasting
  • Data visualization tools

Global Smart Grid Data Analytics Market: Drivers

For the effective use of power generation and effective operation of power systems, smart grid data analytics helps the system run optimized with improved solutions, which drives the growth of the market. Smart grid data analytic market helps the utility providers to analyse the load behaviour and decrease the power cuts. Growing investments in smart grid data analytics and adoption of new technology in companies such as utility providers have many advantages, which help the generation operations. In monitoring stations this data analytics help in terms of providing the huge volume of daily load data, weekly load data so as to identify the demand from the consumer side. To estimate the daily load generation in order to meet the exact demand from consumer end helps the utility sectors load operations. Economic operation from transmission to distribution sectors and reacting quickly in abnormal conditions (such as power failure or short circuit) visualizations of load all these factors accounts for the growth of the smart grid data analytics market.

 Global Smart Grid Data Analytics: Trends

Increasing demand for smart grid data analytics in end-use sectors. Optimizing solutions for the non-linear systems which help in operating the system is one of the key trends. Rise in automation in industries adopting smart meters, sensors, automated system to collect the data and analyse in a pictorial representation and with high visualization helps understand the system behaviour, store the entire data in cloud, access the data and makes able to take decision from remote locations for the utility sectors is one of the key trends for the smart grid data analytics market.

Global Smart Grid Data Analytics: Regional Outlook

The regional coverage of smart grid data analytics market includes North America, Latin America, Europe, APAC and MEA. The smart grid data analytics market is witnessing significant growth in Europe and North America.  Growing adoption of smart grid technologies and effective use of power is one of the key driving factor in North America and Europe.  APAC is one of the fastest growing economies, and upsurges in the manufacturing and industrial sectors, where the high adoption of automation and smart grid data analytics in both the utility and end-use sectors drives the growth of the market. Followed by MEA and Latin America.           

Global Smart Grid Data Analytics Market: Market Participants

Examples of some of the market participants identified across the value chain include Accenture Plc., IBM Corporation, SAS Institute Inc., EMC Corporation, Siemens AG, EMC Corporation, SAP SE, Hewlett Packard (HP) Development Company L.P., etc.

MRR.BIZ has been compiled in-depth market research data in the report after exhaustive primary and secondary research. Our team of able, experienced in-house analysts has collated the information through personal interviews and study of industry databases, journals, and reputable paid sources.

The report provides the following information:

  • Tailwinds and headwinds molding the market’s trajectory
  • Market segments based on products, technology, and applications
  • Prospects of each segment
  • Overall current and possible future size of the market
  • Growth pace of the market
  • Competitive landscape and key players’ strategies

The main aim of the report is to:

  • Enable key stakeholder’s in the market bet right on it
  • Understand the opportunities and pitfalls awaiting them
  • Assess the overall growth scope in the near term
  • Strategize effectively with respect to production and distribution

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