Many utilities find themselves under-prepared for disasters due to constraints within their core IT systems. However, there are techniques and tools they can use to improve their management of disasters, writes Tarun Bhandari
For electrical utility companies, the task of planning and managing the aftermath of natural disasters is a daunting and difficult one, fraught with a multitude of decisions to be made using information from multiple sources.
For the public, however, restoration of power in the event of a disaster is a critical activity and, to many, a life-saving one. If a disaster strikes, millions of people can be affected by the inefficient and uncoordinated efforts of just one organization.
Last month, hundreds of thousands of Texans were without power along the US Gulf Coast as Tropical Storm Harvey made landfall and caused devastating flooding, knocking out power lines.
In June, severe thunderstorms knocked down trees and power lines affecting the supply of electricity to at least 112,000 residents in Kansas City in the US.
During 2016 alone, natural disasters around the world cost utilities combined economic losses of approximately $210 billion in repairs and fines, attributed to 315 separate events. Losses as a result of calamities or natural disasters have risen to the highest levels seen in four years around the world. The question we must ask is: can utilities confidently say that they have a robust disaster operations management plan in place? If not, there might be a steep price to pay.
In order to minimize both disturbances and recovery times to the public when a natural disaster strikes, regulators are imposing heavy fines on utilities for extended outages, which are defined as services not being restored within a stipulated time.
Penalties for damage
In the UK in 2013, SSE and UK Power Networks (UKPN) were fined à‚£8 million ($10.4 million) for management failures of slow power restoration following a major storm, which left almost one million homes with power cuts during the Christmas period. In addition, SA Power Networks in Australia was ordered to pay $20 million in compensation to 75,000 customers who were affected by a blackout following a storm late last year.
It’s clear that regulators are sending a clear message that negligent action, or in most cases inefficient action, will bring strict penalties. The initial costs of implementing comprehensive and robust disaster operations management might be perceived as a drawback by some, but the investment means avoiding lengthy downtime, power restoration delays and subsequent hefty fines from regulators.
As a result of increasing fines, utilities are also having to create contingency funds for such penalty payouts. This means that expensive capital is blocked and cannot be effectively utilized. Utilities face their budgets and operational efficiency being left at risk, and need to respond to adverse weather conditions with accuracy and speed.
During the next three years, it has been predicted that the global incident and emergency management market will grow by over 20 per cent, to $101.3 billion. Major drivers of this growth include changing climatic conditions, increasing government regulations, extensive usage of social media to spread information and the increased threat of terrorist attacks.
An example of the changing climate is demonstrated in the recent modelling conducted by a group of international scientists. Their research suggests that extreme El Niàƒ±o events will become more frequent in Australia over the next century, bringing weather patterns that are associated with droughts, floods and cyclones.
The warning stated that El Niàƒ±o events “would rise from the current five events per century to 10 per century by 2050”. What’s worrying is that the risk will keep on rising for a further 100 years to potentially 14 events per century by 2150. This, therefore, is a crucial point for organizations to prepare for the future.
Overcoming the challenges
Many utilities find themselves under-prepared for disasters due to a number of constraints within their core IT systems. These often include poor integration, limited availability of information and a lack of sufficient time to respond to disasters. When systems are neither intelligently integrated nor intelligently functional, it can cause huge delays to the restoration process. Multiple legacy sub-systems may also operate within silos, with large, complex data sets requiring comprehensive analysis – thus, resulting in many being unable to provide results and offer decisions in near real-time.
Consider the need to analyze the impact that an extreme storm has on a utility’s assets. Data will be required from both a weather service and an asset management system to layer the two together for analysis. Further information could then be drawn from vegetation data to predict the impact of fallen trees on those assets. In order to commence repair, field force automation and workforce management systems would need to organize the dispatch of field crews to repair the damage.
|In 2016 natural disasters cost utilities $210 billion|
This reactive process of responding to a disaster is both time and labour-intensive. It’s also very likely to result in fines for services failing to be restored within the required amount of time.
Costs for the restoration of power also increase further when outdated systems lack the capability to provide an accurate and reliable response plan. These costly overheads may include the hiring of specialists to run damage assessment tests or paying staff overtime to fix the problem.
Laying the groundwork
Regulators are increasingly focusing on utilities’ performance metrics for defining their rates, costs and access to safety improvement, as well as R&D and innovation budgets. All of these affect the utility’s operational and financial performance.
An intelligent DOM solution will also prepare the groundwork to enable utilities to align and prepare themselves for some of the newer changes on the horizon, such as performance based regulation (PBR).
This is being considered with multi-year plans with the aim of incentivizing utilities to modernize their operations and align customer needs with company goals and policy goals. If utilities are able to identify cost savings, this will result in higher returns, but if they exceed their revenue cap, they will incur losses. For example, Minnesota uses a multi-year plan that, according to state legislature, can replace annual rates as long as it bases a portion of utility revenue on encouraging efficiency. Rates are also reasonably in line with the costs of service during the time period.
The introduction of intelligently integrated systems for location-based DOM would provide the assessment and management that utilities require to improve responsiveness. It would enable them to move away from being reactive, towards a process that helps them anticipate, plan and execute methods to reduce the impact of disasters.
Even utilities that proactively mobilize without an outage or damage forecast model get it wrong; most either over- or under-prepare. Predictive damage assessment tools can now leverage Machine Learning, historical and Big Data analytics to improve damage forecast modelling, drawing on past data sets to produce accurate and reliable estimates of the damage that assets can sustain. In addition, by automating processes, they can learn and respond to the evolving climatic scenarios.
The communication between data is strengthened by the integration of formerly disparate systems, such as command control centres, weather information and field damage assessment. A 2016 report funded by the UK’s Department for International Development (DfID) assessed the application of Big Data for climate change and disaster resilience.
It demonstrated how Big Data could be used in the early detection of floods by gathering and analyzing information about flooding from social media feeds with satellite observations. Scientists were then able to build a real-time map of the location, timing and impact of floods. This map is updated on a constant basis.
The latest data sources generated and used by utilities, such as Light Detection and Ranging (LiDAR), 3D imagery and Internet-Of-Things (IoT) sensor data, can also be integrated to enable better decision-making. For example, the use of IoT in the electric power industry enhances the grid’s resilience and durability from outages. Smart meters are used as grid sensors that support decision-making systems in several ways, including demand response, voltage management, outage management, accelerated restoration and overall operational efficiency.
Using the power of data
If utilities adopt a more predictive and data-driven approach, they can acquire the operational power to quickly coordinate with emergency response services. They can also leverage historical data to improve their effectiveness and reaction time in future. Teams are supported with tools to collaborate effectively and remove delays caused by disparate, unconnected systems.
Consumers today are heavily reliant on the electrical grid, and the ‘always on’ world has increased expectations about a utility’s recovery times from outages in the event of a natural disaster. Regulators demand fast reaction times and consumers rely on power restoration as quickly as possible. Adverse weather conditions and threats to public safety are only going to grow. But now, utilities have access to a rich pool of data and intelligent technology to enhance their efficiency and support their efforts to build a strong model for managing disaster operations.
Tarun Bhandari is Head of Location Based Services, Utilities and Geospatial, at Cyient. www.cyient.com