Global electricity grids are undergoing a radical transformation. Large reliable centralized thermal power plants are being replaced by many variable sources like wind and rooftop solar. At the same time, this new capacity is migrating to the edges of the network. Other factors like increasing energy demand, extreme weather events, and emerging influences like the electrification of transport also increase the risk of instabilities and blackouts. Distributed energy resources are also diminishing the level of control network operators have and their status or existence are often opaque at the residential level. Not all utilities even require customers to register their solar systems, for example.
A typical distribution grid control room system already monitors a million different points on the network in real-time. By adding all these distributed energy resources, the need to manage millions more points is looming.
As the number of assets with these different behavior profiles grows, monitoring and adapting to these changes is becoming more important. New technologies and systems are available to provide operators with precise, real-time status of the grid and better situational intelligence to anticipate grid conditions for quick mitigation decisions and actions. Maintaining the grid's stability is nonetheless becoming increasingly challenging due to the pace of change and the increase of the system’s complexity.
More innovative technologies are emerging that support additional control room functionality. Distributed Energy Resource Management (DERM) systems, for instance, are one tool that can allow network operators to aggregate distributed resources effectively, and DERM provides both grid edge intelligence and functionality. Advanced Distribution Management Systems (ADMS) and Wide Area Management Systems and Control (WAMS and WAMC) are also tools that can help with proactive grid stability management. The network control center requires more advanced tools to support system management and ensure supply and demand are always in balance. These tools require all pertinent information to perform effectively. In fact, with millions of potential data points, there are vast volumes of data that operators will use to base their decisions on. Gathering and analyzing the huge volumes of data to find insights and plans of action means that effective grid control is becoming increasingly a data management challenge. In the control room environment of today, preparing and supporting operators to get the most out of the new tooling suite is vital to network stability.
New Tools and New Techniques
While the complexity of the network has grown, the capabilities of related control systems have also dramatically increased. Alongside supporting frameworks like ADMS, WAMS, and DERMS, new fields such as machine learning means that a whole range of better grid management tools are now available. Artificial intelligence, for example, is adept at sifting large volumes of data and drawing actionable conclusions from these resources. Adding these kinds of intelligence-led decision-making tools to control room systems is vital to ensure reliability. Still, we also need to prepare operators to use them to be more proactive and not be overwhelmed with data. If there is a significant event, operators could receive hundreds or even thousands of notifications over a short period. This phenomenon, known as an alarm cascade or swarm, can make it extremely difficult to determine the root cause of the failure and take appropriate action.
There are several techniques to support real-time alarm analysis, though, for example, the Network Event and Alarm Transparency (NEAT) project saw PSC and data science company Harmonic Analytics create a tool for diagnosing alarms and events to support Distribution Network Operators (DNOs) manage the increasing number of new and unfamiliar alarms in their control rooms. Developed for the UK’s Western Power Distribution (WPD) network operator, NEAT helped them understand the root causes of the alarms and enabled them to be managed more effectively.
The grid stability and control issue is expected to become far more complex over time - as is the scale of the computer software systems that are required in response. For instance, scaling the databases needed to model the evolving grid. Operators must keep those systems current to handle the sheer volume of data. While the grid balancing challenge is scaling up, utilities have a crucial advantage as they have typically already amassed substantial volumes of network data. This is the first step towards better control.
By correctly understanding and using the available data to deliver the right insights, it is possible to manage the network more efficiently. That could, for example, potentially avoid the need to invest billions of dollars on transmission infrastructure needed to reinforce the grid. Indeed, investing in smarter analytics can be a fraction of the cost of avoided infrastructure upgrades.
So, in addition to the new and more advanced tool sets that are required, investing in operator training is also vital. Dispatcher training simulators are an excellent approach to help prepare control room operators for ‘real-time’ scenarios. Ultimately, the control room is the center of the network management system and operators are the experts of the system. Given the scale of the challenges, we must do more to ensure they are fully prepared and able to maximize the value of the available data.
Getting Smarter with Control Room Systems
While investing in a better understanding of the network and putting appropriate control room tooling in place is preferable to the alternative outcomes, operational goals can only be met with a substantial up-front investment in data science and related control systems. Partnerships that bring data science and analytics experience to bear can support network operators as they try to find more effective ways to manage what is the largest machine in human history. Like any complex system, it takes teams of people to have a solid understanding of all the different facets of the grid.
Network operators increasingly recognize the value of this approach. For instance, ATCO Canada has 229,000 customers in north and east-central Alberta and wanted to expand their view of the transmission system by enhancing their Energy Management System (EMS) to respond to the changing reality of network operations. By better understanding their existing transmission system tools and capabilities, they could establish that they already have an appropriate EMS platform with capabilities that could be extended. This gave them various options that could be explored over the coming years to enhance their capabilities without significant investment.
Elsewhere in North America, the US PJM TSO coordinates the movement of electricity across 13 states and the District of Columbia and serves some 65 million people. Since 2011 it has relied on its Advanced Control Center to provide mission-critical energy management system (EMS) functions and market management systems (MMS). However, during the rollout and implementation of the system, PJM relied on experienced partners to help smooth the development process between the customer and the system vendor and ensure that the program was timely and still met its overall objectives.
Data science projects require trust to get launched as the outcomes are not predefined. The good news is that a data science project can be scaled down to give it a chance of returning value quickly and prove data science’s effectiveness as a valuable business tool. The challenge of the energy transition is that the required pace is immense. As an industry, the transmission and distribution sector must be more nimble to leverage lessons already learned to move quickly. At its heart, the wires game has evolved, so grid operators must too. Implementing the control room systems necessary to manage the increasingly complex and evolving network landscape effectively is critical, but learning how to use those systems effectively is imperative.
Alex Boyd is President & CEO at the PSC Group.
