The effective application of power big data can provide a large number of high value-added value-added service services inside and outside the industry, which has high value for the improvement of the profitability and control level of power companies. According to an analysis by grid experts, whenever the data utilization rate is increased by 10%, the grid can be increased by 20% to 49%.
McKinsey has reported that globally, the widespread use of big data analytics solutions can result in $300 billion in annual electricity bill cuts. The effective application of power big data can provide a large number of high value-added value-added service services inside and outside the industry, which has high value for the improvement of the profitability and control level of power companies. According to an analysis by grid experts, whenever the data utilization rate is increased by 10%, the grid can be increased by 20% to 49%.
The data source of the power industry mainly comes from power generation, transmission, substation, power distribution, power consumption and dispatching. It can be roughly divided into three categories: one is grid operation and equipment detection or monitoring data; It is the marketing data of power companies, such as transaction price, electricity sales, electricity customers and other aspects; third, power enterprise management data.
Through the use of smart terminals such as smart meters, the operating data of the entire power system can be collected, and the collected power big data can be processed and analyzed systematically to realize real-time monitoring of the power grid; further integrating the big data analysis and power system model to the power grid Operation for diagnosis, optimization and prediction to ensure safe, reliable, economical and efficient operation of the grid.
First, grid monitoring and maintenance1. Operation and maintenance monitoring system responds in time
Enphase Energy collects approximately 2.5 terabytes of data per day from 250,000 systems in 80 different countries. This data can be used to detect power generation and facilitate remote maintenance and repair to ensure seamless system operation. In addition, Enphase Energy uses data collected from power generation systems to monitor, control, or adjust power generation and load conditions in the network, reacting to changes in the grid and in the event of an error or upgrade.
2. Special analysis of equipment operation and maintenance
Power companies can conduct in-depth analysis of each business area based on a one-stop big data analytics platform.
For example, in the field of power grid operation and maintenance, through the management of power equipment assets, equipment inspection management, equipment technology management, technical reform overhaul management, etc., key indicators are selected from three aspects of safety, efficiency and cost, and analysis and maintenance management The interaction between safety, efficiency and cost is coordinated and optimized. At the same time, real-time online monitoring of maintenance indicators of power grid enterprises is realized, which provides guidance and services for the company's maintenance strategy and realizes intelligence. The inspection system is just around the corner.
3. Prevent power outages caused by basic equipment failures
At the Asset Health Center at American Electric Power Co., Inc. (AEP), data analysts combine device-derived operational information with intelligent information applications. By using big data algorithms and analysis software, they can closely monitor the operation of the transport infrastructure.
Today, AEP uses robust meters, communication networks, and data management systems to get robust, regular information. Smart grid technology enables customers to use electricity more efficiently and manage the cost of electricity. The collected data also helps the company customize power management procedures and provide customized services.
Second, improve operational efficiency and improve customer experienceBig data analytics can help power companies improve operational efficiency and improve customer experience. Operational benefits include revenue assurance, network and product management, demand forecasting, asset management, and support function optimization. Similarly, analytics can help improve the customer experience through customer relationship optimization, proactive marketing, and customized offers and services.
1. Gulf Power (Gulf Power Company, a branch of the US Southern Power Company in Florida)
Gulf Power used big data analysis to confirm that if there is a power outage, the time to restore power can be 10 minutes earlier than the expected time of the user, and customer satisfaction is the highest.
Interestingly, it found that if power was restored more than two hours before the expected return to power, it would have a negative impact on customer satisfaction. Understanding indicators like this can help power companies solve their biggest customer experience challenges. An executive at a German power company confirmed that improving customer satisfaction would increase customer retention.
He explained, “Analysis allows you to communicate with your customers on personalized contracts with personalized offers. This approach will significantly increase customer retention.â€
In fact, power companies like EDF Energy have reduced customer churn through big data analytics, saving up to $30 million annually.
2. Lakeland Electric (United States Lakeland Power Company, based in Florida)
Load research is a process used to analyze the customer consumption patterns of various customer groups (home, business, and industry), and it helps to assess the cost of power companies serving each particular group. Researchers believe that using AMI (Advanced Metering Architecture) and data capture capabilities, every metering point and smart grid enabled device may help with this research. Lakeland recently used these new technologies to complete cost checks on electricity services. In addition to addressing the need for additional revenue, they are able to design alternative rates for customers to choose from, while reducing power peak demand, and on the other hand, customers save money in the process. It not only effectively reduces the power failure during peak hours, but also enhances the user experience, improves the user retention rate, and enables the company to have a better reputation and popularity.
3. Effectively improve the marketing service level of the power industry through data analysis
Power users can provide more detailed data to the business department based on the one-stop big data analysis platform, and the business department completes the data application from the service.
Through the analysis of customer service and customer relationship, electricity bill management, energy metering and information collection, market and orderly power consumption, new business, and integrated management, we will grasp the development of key tasks in marketing business and realize customer service and electricity bill management. Effective monitoring of smart meters, orderly electricity implementation and energy efficiency management effectiveness, new business and marketing audit work quality indicators.
Third, reduce losses, reduce costs1. Reduce power theft and reduce losses
According to Northeast Group, LLC. (Northeast Group, Inc., Washington, USA), "Energy Market Smart Grid: 2015 Outlook Study" reports that global power loss was $89.3 billion annually. And smart grid technology can help power companies fight millions of power thefts every year.
Enel, based in Italy, is one of the world's largest power companies with 670 million meters in 40 countries. In Italy, Enel integrates data from more than 50 billion lines of 11 legacy systems and has identified 93% of the theft or other non-technical losses, the world's largest smart grid analysis system. In Italy alone, its annual income protection and predictive asset maintenance analysis is estimated to cost more than 350 million euros.
2. Use analysis to reduce transformer replacement costs
PSE&G (Public Service Power and Gas Company) is one of the largest integrated power and gas companies in the United States, serving 1.8 million gas users and 2.2 million power users. It has assets worth about $17 billion and revenues of nearly $8 billion.
PSE&G implemented a Computerized Maintenance Management System (CMMS) to assist with repairs, replacements, and maintenance decisions for assets including transformers and other equipment.
According to various factors such as humidity, dielectric strength, flammable gas change rate and cooling performance, the transformer is analyzed to generate equipment condition scores. They use the asset replacement (predictive) algorithm to analyze the equipment condition score and other factors (age, spare parts availability) to determine the appropriate time to replace the transformer.
PSE&G also uses advanced analysis of real-time sensors to track various operational metrics. The application of the analysis helped the company identify and remediate problems before they occur, saving millions of dollars in avoiding equipment failures. The company also decided to actively replace some of the transformers by using an analytical model instead of replacing it after a problem, which helped the company save more than $100 million in 25 years.
New information technologies such as big data analysis will certainly activate the value contained in power big data, and will also release the market potential of power big data. According to GTM Research's research and analysis, by 2020, the world's power big data management system market will reach 3.8 billion US dollars, the power big data collection, management, analysis and service industry will usher in unprecedented development opportunities.
Under such opportunities, more power companies will choose to actively explore big data analysis technology, enterprise system operation and maintenance monitoring, improve customer satisfaction, reduce losses and costs.
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