The challenge of meeting future energy demands – caused by a lack of new power plants to replace those being decommissioned – means utilities are having to rethink how they operate. This predicted energy crunch is challenging on two levels. First, it has encouraged the growth of competing forms of energy, such as in-home renewables and localised generation facilities, Second, it has encouraged greater regulation.
Through its RIIO regulatory framework, Ofgem has mandated pricing controls over the next decade in a bid to make sure that gas and electricity distribution companies manage energy more effectively and sustainably in the coming years. As a result, network companies face an unprecedented challenge in securing adequate investment to maintain a reliable network while managing an increasingly volatile generation portfolio. Ofgem has also threatened significant penalties for energy network companies that fail to address the needs of vulnerable consumers.
On the flip-side of the regulatory stick, there is also a substantial carrot in the form of incentives for network investment and ensuring consistency of supply.
The good news for distribution network utilities is that data analytics stands to deliver many answers to both the threats and opportunities posed by the modern energy market. In the case of constancy of supply, smart meters and big data analytics systems can help utilities to better understand how power is being produced and consumed across their networks, and help them avoid shortages.
For the modern energy retail company, the key is being able to accurately balance retail supply with consumer demand, because even a small imbalance can have a huge impact on profitability and expose the company to higher risk. The analysis of smart meter data can help by providing a wealth of information on how energy is actually being consumed, which in turn enables energy companies to predict demand more accurately and manage their contracts with increased confidence, which will allow them to ultimately adopt more aggressive pricing strategies.
This is particularly powerful when predicting demand during peak periods, because energy companies have traditionally needed to purchase additional capacity to satisfy excess consumption, often at short notice and for significantly higher prices.
Data analytics allows both retail and network utilities to uncover new insights about how energy is consumed and distributed across the network, while gaining deeper insight into how to improve the efficiency of that process. At the same time, smart meters stand to offer significant value to consumers, providing them with granular information on how they are using their power and flagging areas where they might be able to conserve energy and cut costs.
This collection and conversion of smart meter data into actionable insights for customers can provide them with the impetus they need to make small changes in behaviour – replacing water boilers, lowering their thermostats by one degree in the winter, insulating walls – which can translate into significant reductions in their long-term consumption. For a customer base that is more cost-conscious and ecologically aware than ever, energy providers’ ability to help them become more energy efficient is hugely important, and will go a long way towards helping them build brand loyalty.
Additionally, engaged and informed customers will be more inclined to curb their energy use on peak days, which means energy providers may not be forced to buy so much additional power to cover additional peak period demand.
Customer engagement therefore holds the key to both cost reduction and improving consumer relationships for both retail energy and distribution network utilities.
Improving consumer relationships is particularly important when it comes to social media. In the age of Twitter and Facebook, effective social media engagement is critical for energy companies. A single complaint can attract millions of views within minutes and generate hugely negative publicity for the company involved. Customer service must therefore be exceptional and any faults repaired as quickly as possible.
Smart meters and data analytics can also combine to create a meter management system that can immediately flag faulty devices so they can be repaired before the customer notices the issue in the form of a “bad bill”. More accurate meter readings mean that fewer customers will be billed incorrectly when things do go wrong, which in the best case can prompt customers to phone in their issues, and in the case of widespread inaccuracies can see retailers incur heavy fines from the regulator.
Data therefore holds the key to success in the modern energy market. The success of the smart meter rollout, however, will largely depend on the extent to which utilities are allowed to collect and manage the information that these tools have the capability to provide them.
In the UK the rules governing utility companies’ access to smart meter data are still being finalised, but the indications are that energy providers will not automatically gain access to customer consumption data, because businesses and households will have the option to opt out of sharing this information with them.
Energy companies therefore need to plan their smart meter strategies carefully to maximise the value of the information they collect, while remaining compliant with evolving privacy policies. If they can do this successfully, the result will be a more efficient and sustainable energy future for suppliers and consumers alike.
Mike Ballard, senior director utilities strategy at Oracle EMEA