Load-shedding is a fiery topic of debate across South Africa at present. However, an insufficient power station capacity to supply customer demand (load) causing the electricity system (grid) to become unbalanced and collapse, is not the only reason for blackouts experienced throughout the country.
Risks to the grid also include severe weather conditions, short circuits, faults at power stations, damage to- or theft of electric transmission lines, and more, causing both short- and long-term loss of electric power to an area.
The quick restoration of power for business and personal productivity becomes especially important when the environment and public safety are at risk, but this unfortunately is not always an easy task.
According to the white paper by Schneider Electric, “How to ensure accurate analysis for faster, more efficient service restoration”, traditional grid outage management systems suffer from two fundamental flaws: they lack an accurate, current representation of the grid network model and they typically don’t integrate with the systems that monitor and control the actual grid. These shortcomings result in longer outages, higher costs, and in lower levels of customer service.
John Dirkman, senior product manager for Smart Grid Global at Schneider Electric and author of the white paper, says that utilities use outage management systems (OMS) to manage the grid and restore power during a service interruption. “An OMS identifies and predicts potential grid outages and manages restoration activities with the goal of reducing the economic impact of power outages,” he says.
Dirkman adds that the most advanced systems can reduce downtime and corresponding costs by up to 25 percent, but a traditional OMS has two basic shortcomings: lack of a real-time representation of the smart grid network model; and ineffective or no integration with the systems that monitor and control the grid. Although an OMS may function as expected, these gaps result in a fragmented network view for system operators that can lead to human error, unnecessary complications, and less-than-optimal workflows. Dirkman elaborates on the two shortcomings as:
An evolving network model
He says that the prime objective of an OMS is to understand where a utility’s customer fits into its network, in order to analyse the location and extent of an outage. An accurate analysis depends upon the network model mapping out customer connections. But maintaining an up-to-date model of the operational grid in an OMS is not simple. Distribution systems undergo daily changes due to operational configuration, network additions, and routine maintenance switching. Changes can originate from different sources, such as control centre operations, maintenance and construction crews, and service personnel. An obsolete network model can cause an OMS to misdiagnose an outage – which results in sending repair crews to the wrong location and extending the duration of an outage. Furthermore, operators may come to distrust or even discount the information an OMS provides.
Integration of disparate tools
Dirkman adds that when systems integration is lacking, operators don’t have a clear view of their network. Many utilities create “workarounds” to compensate, frequently using a manual process to shuffle information from a SCADA system and/or distribution management system (DMS) to the OMS and back. This convoluted bidirectional navigation between systems can impact dispatching and cause mistakes and poor decisions during outages. However, integrating real-time tools like a SCADA system or DMS with an OMS is problematic. Utilities prefer to operate their command-and-control systems on stand-alone, closed-loop networks to ensure performance and security. In addition, operations business units control these mission-critical systems rather than centralised corporate IT. This can result in less focus on standards and integration architecture, which can further complicate any integration initiatives.
“With millions of network data points to process and various distributed energy resources to integrate, a traditional DMS cannot analyse the high data volumes needed to manage a smart grid. Instead, many utilities rely on an advanced distribution management system (ADMS),” says Dirkman.
An ADMS places the tools for outage analysis and crew dispatch alongside those for control, load flow, and grid optimisation, which promotes a more responsive and less error-prone workflow. An ADMS eliminates the network modelling problem, enabling OMS functionality against the memory-resident, real-time model of SCADA / DMS. A single, high-performing network model for SCADA, DMS, and OMS improves accuracy and performance, and eliminates the need for data synchronisation among disparate models.
He advises utilities and concerned stakeholders who wish to initiate a migration to an ADMS approach to consider the following short and long-term steps:
* Within the next few weeks – begin to plan a migration roadmap. Assess what steps need to be taken in order to evaluate current outage management weaknesses. Conduct an assessment of requirements.
* Within the next six months: Determine how much work needs to be done to implement a cutover to ADMS, what the cost savings will be, and what the impact will be on both operators and customers. Consider how existing systems can complement the new network control engine.
* Within the next year: Enlist a trusted partner with expertise in both grid management systems and operational efficiency to help maximise modernisation benefits via ADMS.
“A smarter grid will require robust tools to manage both normal operations and emergencies. Outage costs are too high and both business and home consumers demand a higher level of grid uptime. Traditional OMS that is poorly integrated with the real-time environment and based on a less-than-current network model will struggle to fulfil the need. By providing a single environment and user experience for SCADA, DMS, and OMS, ADMS tools and applications can enhance outage performance with better decision support and workflow. This elevates the development of the grid and simplifies the work of people who are tasked with grid operation,” concludes Dirkman.