Smart energy systems – and new business models

Smart Energy pictureStefano Mantegazza, Head of Industry, Services, Energy and Retail at NTT DATA looks into the future of smart energy and the use of new business models and new technologies.

NTT DATA is using its experience in the energy sector, combined with its extensive work with other utility providers with similar needs such as telcos, to help transform the European energy industry.

The energy industry is currently in flux. The introduction of new business models and technology is key to successful smart energy strategies. The latest International Energy Outlook predicts that worldwide energy demand will rise by 56% by the year 2040.

Energy companies currently have to deal with rising energy prices in the face of expanding demand along with environmental and regulatory pressures. Renewable energy sources are reducing the reliance on fossil fuels, but creating a more complex and unpredictable energy source landscape.

The introduction of new business models and technology is absolutely necessary to overcome these challenges.

In short energy management systems need to become intelligent. When information technology is used to overlay intelligence onto the electrical grid, it becomes possible to gather and react to information on supply demand and grid optimisation.

Collecting data about the behaviour of suppliers and consumers in an automated fashion, can improve the efficiency, reliability, economics and sustainability of the production and distribution of electricity.

Focusing on generation

Because storing energy on a large scale is not currently feasible, grid stability requires a balance between power consumption and creation. ‘Virtual power plants’ work by co-ordinating power consumption and generation more effectively. A centrally controlled system of an interconnected facility connects the various elements of renewable, traditional and micro-generation, to respond to fluctuations on the grid and ensure that an optimal power output is maintained.

As well as smarter plant design, the development and implementation of forecasting modellers can ensure more balanced production to better match user needs and changes in demand.

The sophistication and speed of modern data analysis tools means that modellers can now offer insights that provide much more accuracy and ensures production (supply) is more closely linked to demand.

This is especially important, as regulation has introduced huge costs to the energy companies related to the network latency. In essence, new rules are underway that make the producer pay when energy is not balanced. The end result is that near real-time monitoring of supply and demand is going to become crucial, as is the ability to model usage patterns in order to accurately predict demand, and shape energy supply accordingly.

When rolled out throughout the business, business intelligence solutions can ensure more efficient production from every source. These can even start to look for problems before they occur and proactively manage potential issues.

Trading, retailing and distribution

Distribution is the second part of the equation. Currently, most operators work very reactively when it comes to the maintenance and repair of power grids. But as demand grows and the flow of power becomes increasingly bi-directional, so the automation of network maintenance and repairs is going to become critical to minimising service disruption to users.

Tapping into the data within the network that intelligent supply demand and grid optimisation can offer, will allow providers to look for problems before they arise and fix them before they become an issue.

This intelligent insight into the distribution network can also be pivotal in ensuring balance in energy supplies to match ever-changing user demands. Traditionally, power demand had been dynamic while production has been relatively static. But when an intelligent communication layer is added into the grid, it becomes possible to transform the energy distribution and dynamically allocate energy where it is needed. This is particularly useful when considering integrating input from consumer micro grids back into the larger network.

Optimising operations

The final piece of the puzzle occurs at the point of consumption – within the home or business. The introduction of advanced metering infrastructure, such as smart metering, provides more insight into customer usage and encourages more accurate billing and better load balancing across the network.

In those places that still use analogue meters, the usage has to be managed manually. This either involves consumers reading and submitting readings or a member of the energy company’s workforce coming round. This is a laborious manual process and usually only gets done a few times a year. Not only is this expensive but, with so few data points, gathering any intelligence on energy usage is almost impossible.

Smart metering enables energy companies to manage infrastructure assets with significant cost savings. Energy usage is automatically transmitted back to the provider, on a regular and frequent basis, providing far better insight into actual usage and customer behaviour.

Conclusion

To thrive in the complex, shifting and high regulated environment of the energy sector, companies need to optimise their business processes and IT solutions to address operational, commercial, and energy management challenges.

This requires new levels of deep intelligence to be inserted to every aspect of the production, delivery and consumption of energy. From smarter plant design and maintenance, more effective energy trading and dynamic power distribution and load management through to intelligent usage and micro-grid generation.

This is beneficial for both consumers and energy and utility companies, improving the overall user experience through improved insight and more personalised services. This is the future of smart energy.

 

 

 

 

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