By Jay Giri and Manu Parashar
The typical large power system grid is a complex engineering machine that consists of millions of components. Its mission is to provide electricity around the clock to a large number of geographically dispersed customers. Continual changes in customer electricity demand necessitate instantaneous changes in electricity production. Hence the grid is perpetually in a state of flux and conditions are constantly changing every second of the day. The challenge of grid operations in this dynamic environment is to ensure that power system operating conditions stay within safe limits at all times.
The energy management system (EMS) in an electric utility’s control center manages operation of the high voltage transmission grid. The mission of EMS operators is to ensure electricity is available to all customers at all times. At the EMS, grid conditions are measured every few seconds and unsafe conditions are identified and alarmed. Timely visualization of grid measurements is essential for successful grid operations. Real-time measurements then need to be intelligently converted into actionable information. Grid operators do not just need to know that a problem exists. Operators need to fix the problem!
Future grid operation challenges
Today, operating the grid is becoming even more challenging due to many new trends. These include:
- Adverse weather patterns becoming increasingly severe;
- Demand response programs and customer engagement unpredictably changing load;
- Distributed generation resources with energy outputs that are difficult to predict;
- Electricity market systems resulting in more unpredictable electricity flows;
- Generation company decisions that may be independent of the transmission company decisions;
- Challenges in forecasting load, generation capacities and operating margins; and
- Maximizing utilization of existing grid assets resulting in operation closer to equipment limits
Fortunately, new technologies and solutions are being developed to address these issues. Two such key solution domains are the focus of this article. They are enhanced visualization of grid conditions, and enhanced automated grid control.
Enhanced visualization of grid conditions
For many decades, the EMS has monitored grid conditions via Supervisory Control and Data Acquisition (SCADA) every two to four seconds. Today a new cadre of grid measurements is rapidly growing worldwide. Called “synchrophasor” measurements, they monitor the grid at a rate of 50 to 60 samples per second using hardware called phasor measurement units (PMUs). A global positioning system (GPS) satellite time clock is used to precisely “time-tag” these measurements. This allows for much faster monitoring of power system conditions. The fast PMU data augment the traditional two to four second EMS SCADA data. Although PMUs are small in number today compared to SCADA measurements, their numbers are growing at a rapid rate worldwide. The modern EMS for future grid management consists of both SCADA and PMU data.
One challenge for grid operators in this dynamic new environment is to concisely present this voluminous sub-second PMU data for operator decision making. A frequently cited human limitation has been described as Miller’s “magical number seven, plus or minus two.” Miller’s observation was that humans have a limited capacity for the number of items or “chunks” of information that they can maintain in their working memory. As the saying goes, a picture is worth a thousand words. More importantly to grid operators, the correct picture is priceless! This means creating a concise picture of what needs immediate attention is immensely more beneficial. Dynamic dashboards are a way to alert operators of current priority concern areas.
Enhanced automated grid control
For decades, the power grid has been operated on an essentially ‘reactive’ paradigm. Current EMS real-time conditions are the basis of determining actions that will ensure grid reliability and security. Cognitive behavior methods have been utilized to develop operator ‘use-cases’ to document the specific sequence of actions an operator takes in order to accomplish a specific task. These can be used to develop optimum navigation capabilities (such as the least number of key-strokes to quickly go from receipt of an alert, to analyzing the ‘correct picture,’ and to implementing the appropriate control action.
Today’s wide area monitoring systems (WAMS) have implemented advanced PMU-based analytics. These include fast monitoring of angular separation, oscillatory stability, voltage stability and islanding detection. These solutions bring additional situational awareness for the grid operator.
Future grid management is moving toward being more proactive by more closely integrating fast synchronized measurements (such as PMUs) with fast thyristor-based controls such as such as high voltage DC transmission (HVDC) and flexible AC transmission system (FACTS). Today, a variety of fast-acting controls are available that can respond at a sub-second rate to triggers from PMU analytics that detect sudden grid problems. These fast control devices are capable of mitigating a variety of problems such as voltage regulation, phase balancing, congestion relief, poorly damped oscillations, voltage instability, angular instability, etc.
The next step is to augment the existing WAMS applications to perform “what-if” predictions and to suggest corrective control actions. Using angular separation monitoring as an example, Line Outage Distribution Factors (LODF) allow computation of the post-contingency angles across a pre-defined set of contingencies. Then model-based sensitivity analyses can provide a quantitative ranking of operator actions (such as raise or lower generation) in order to reduce the angular separation and restore them to acceptable limits.
Similarly, the WAMS Islanding analytics which quickly detect an islanding condition, can be augmented to analyze network topology to identify the specific island boundaries, provide an assessment of the available resources within each island to stabilize the island, and recommend possible options for subsequent resynchronization of the grid.
Grid operators need a thermostat, not a thermometer
Monitoring is essential, but corrective action is the eventual goal. In other words, we need to transition grid management from just being a thermometer, to becoming a smart thermostat.
Today, such solutions are feasible. For example, a regional utility is working with a vendor to implement a flexible programmable controller platform with a guaranteed response time suitable for automated wide area control solutions. This control platform is designed to be flexible so it can evolve over time to meet future challenges.
Advanced automated grid control will initially start at substations with local information and local controls. In the future, this will transition to a more wide-area implementation, with an underlying ‘think global, act local’ philosophy.
For a downloadable copy of April 2016 eNewsletter which includes this article, please visit the IEEE Smart Grid Resource Center.
Jay Giri, IEEE Fellow, is Director of Power Systems Technology and Strategic Initiatives at GE Grid Software Solutions in Redmond, Washington, USA. He is a group manager for engineers who deliver software applications to utility control centers for electricity market systems, generation monitoring and control and synchrophasor/phasor measurement unit (PMU) analytics. He is a liaison for university research activities and an affiliate professor at the University of Washington. Jay and 11 other engineers co-founded Energy System Computer Applications (ESCA) in 1978. After numerous corporate mergers, ESCA became part of GE Grid Software Solutions in 2015. Jay designed and implemented the original software for the ESCA automatic generation control (AGC) and dispatcher training simulator (DTS) power system simulation functions. Today this AGC controls over 50 percent of North American generation as well as generation in many other countries, and the DTS is one of the predominant simulators used by control centers worldwide. He has a PhD from Clarkson University in New York and a B.Tech from the Indian Institute of Technology (IIT), Madras. He was elected IEEE Fellow for "contributions to the design and implementation of power system control centers” in 2002. Since 2011, Jay has been a member of the IEEE Power & Energy Society (PES) Governing Board – now focussing on Industry Outreach. Jay was appointed Alstom Grid Senior Fellow in 2013 and a member of the Washington State Academy of Sciences in 2015.
Manu Parashar is a senior software manager at GE Grid Solutions (formerly known as ALSTOM Grid, Inc.) where he is responsible for the Wide Area Monitoring Systems (WAMS) and Grid Stability product line. He has been involved in the research and development activities of GE’s Stability Solutions, including synchrophasor applications, and was the technical lead in delivering these applications to North American customers. Prior to joining GE, he was with Electric Power Group where he was responsible for all synchrophasor related research and development initiatives, including leading the development of the real time and offline synchrophasor applications. Manu has been active in various technical forums in North America such as the North American SynchroPhasor Initiative (NASPI) and IEEE Power Systems Relaying Committee (PSRC).