Data Analytics and Energy Efficiency

Smart meters allow for greater insight into the energy use patterns of consumers and provide them opportunities to adjust their energy usage to become more energy efficient. Smart meter technologies act therefore as enablers of energy efficiency by making available information regarding energy consumption, which may lead to the adoption of more efficient habits by the consumers. As a result of greater access to information, consumers increasingly desire more control of their energy consumption; they want to have the power to make their own energy choices. Consequently, access to better information enables the consumer to act in ways that would induce energy savings.

However, smart meters currently do not have the capability to provide the average consumer with enough information to make the optimal energy efficient choices. While the meter directly communicates energy usage with a utility company, most consumers do not know how to analyze the meter data nor do they have access to that data. For this reason, accurate interpretation of data is needed to facilitate the consumer’s choice making capabilities.

Although smart meters can act as enablers on achieving higher levels of energy efficiency, the development of an intelligence layer that leverages on energy metering data and translates it into easily understandable terms is of critical importance. The raw meter data can be a complex endeavor and data analytics services can help interpret this data to the consumer so that the consumer, armed with information, is able to truly make more intelligent choices.

The benefits of data analytics for Energy Utilities

Beyond the most common known benefits from smart metering infrastructure like for instance the capability to eliminate estimated bills, improve outage detection, reduce costs of on-site metering, and improve the balance between energy demand and production, smart meters alone do not go far enough on providing the final energy consumer with the necessary information to become more efficient in terms of resource usage. Nonetheless consumer expectations and demands are constantly changing. Consumers are starting to desire more perks such as personalized services from their utility company, as well as personally tailored products and loyalty programs.

According to an Accenture study, businesses across various industries are increasingly engaging data analytics to gauge consumer insights and are finding analytics capabilities indispensable to resolving business challenges. The study predicts that in order to be a leader in the industry, to continue developing valuable products and not fall behind, energy providers will need to master data analytics in the near future.

Data analytics can benefit Energy utilities in the following ways:

  • Improve customer targeting and segmentation. Understanding consumer behavior and the needs of customer groups is key to successful retention of customers in an increasingly competitive market. Through targeting specific customers, companies are able to discern customer use patterns, and develop and deliver their message more effectively to customers.
  • Effectively target energy efficiency programs. A deeper understanding of how consumers effectively use energy empowers energy utilities to develop targeted energy efficiency programs (that allow to meet regulatory conditions such the EU Directive on Energy Efficiency),
  • Better estimate energy savings and offer appropriate demand management programs. Reliable and quantified information leads to trust and increase of effectiveness of energy demand side management programs through a higher end user engagement.
  • Offer effective, flexible tariff and rebate programs. When customer usage is studied, better decisions about what incentives to offer can be made.
  • Improve billing and payment options. When more information is known about users, companies are able to customize billing to segments of users based on rate class, program participation, interests, efforts to conserve energy, etc.
  • Prevent customer churn. Traditionally, customer loyalty in utilities is lower than in other industries. Bain & Company recommends a consistently designed customer experience by streamlining billing and innovating on the services provided to customers. In return, customer loyalty will help companies build a more profitable business.
  • Prevent energy theft. Smart meters already offer better tampering resistance, but analytics can help advance the detection of power thieves thus preventing revenue losses. Analytics checks monthly consumption and energy bills, and identifies any discrepancies that help detect fraud.

Looking at the consumer side of the equation

Data analytics from smart metering data can offer valuable insight about consumers and their behaviors when it comes to their energy use. Using smart meter readings, analytics can interpret that data to learn about consumer’s preferences and interactions, and can use this information to develop customized messaging and communication with the consumer to provide greater value.

Studies show that consumers actually want to be involved in energy management. Accenture found that consumers highly valued choice and convenience and actually preferred that businesses collect information about them to improve their experiences. They also appreciated customized offers and tailored solutions such as services that highlight the specific actions to take to become more efficient and reduce their energy bill, or the identification of abnormal energy consumptions.

In this sense partnerships with data analytics providers can be key to improving consumer satisfaction and involvement in energy management.

Data analytics can provide consumers with the following:

  • Tailored analysis of smart meter data can help consumers discover where they can adjust their behaviors and adopt new habits. Data analytics can provide consumers with access to the smart meter so that they can understand real-time data that is collected by the meter.
  • Specific recommendations about what that particular consumer can do to save energy. For example, a different set of recommendations is offered to renters and homeowners as their incentives vary. A homeowner may be advised to buy energy-saving equipment while a renter may be given tips to change certain habits.
  • Suggestions about when it is appropriate to invest in new technologies. For example, if the consumer is using a less-than-efficient refrigerator, data analytics tools can determine exact monetary savings that would be possible with an investment in the new appliance.
  • Analytics can disaggregate energy use down to the appliance level. Adopting Non-Intrusive Load Monitoring methods over smart meter readings can help determine which appliances are using the most energy and where energy savings can occur.

Through advanced visualization techniques, smart data analytics is enabling a wide range of new value-added services for the entire energy demand and supply value chain. These data insights will unlock savings opportunities and help businesses provide greater value.

By | 2017-01-02T17:35:41+00:00 January 2nd, 2017|Data Analytics|0 Comments