Autonomous systems and intelligent agents in power system control and operation, C. Rehtanz, Springer, Berlin, 2003, 304pp, ISBN 3-540-40202-0 (2006)

The book Autonomous Systems and Intelligent Agents in Power System Control and Operation by Christian Rehtanz provides a current overview of robust approaches to power system automation and control system autonomy, and uses a number of contributors to discuss key topics. The 14 August, 2003 US–Canada blackout emphasized the need to develop self healing and intelligent power systems that seamlessly react to faults, reducing the need for manual interaction and allowing these efforts to focus on optimizing system operation. With the onset of concerns over power shortages due to aging infrastructure and increases in demand, the desire for alternative forms of generation have seen increasing interest but require an intelligent automated approach for sharing and integrating resources. The relevance of this book is demonstrated by the vision of the IntelliGrid Consortium, which is guiding research that focuses on many of the same concepts, promoting advances in electronics, control and power technology to create a reliable power grid that utilizes distributed energy resources (DER). Chapter 1 introduces the reader to the overall architecture of an autonomous, multi-agent control system. Functionally, this architecture includes the management and organization, coordination and execution functional layers. The structures of the control system are divided into a hierarchical, multi-agent or meshed, which is a combination of the two. The hierarchical structure provides global information between hierarchical levels for action by lower levels, whereas the multi-agent structure acts on available data within its hierarchy or local level. Autonomous systems place more responsibility for action on the lower hierarchy levels, improving the efficiency of interaction and response time. Sharing of information between autonomous agents or hierarchical levels is dependent on open and effective communications. Chapter 2 provides an overview of the open communications protocols currently in use and under development. Based on the open systems interconnection (OSI) layer model, these include the existing TCP/IP and two utility-specific Inter-control Center Communications Protocol (ICCP), IEC-60870, and substation communications, IEC-61850. Web-based technologies are gaining increased interest for transmitting data, such as OLE for process control (OPC) using the Extensible Markup language (XML). Discussion is provided about security considerations, as use of open systems also provides responsibilities to secure data and control from malicious interaction or attack. Chapter 3 provides a brief discussion of intelligent techniques or soft computing control strategies that are available. Autonomous agent interaction is also discussed, as control action can be based on local as well as global philosophy and these interactions can be cooperative or require negotiation. Chapter 4 provides a review of negotiation theory, a necessary component for multi-agent relationships. Several techniques are discussed, including computer techniques such as MASPower, a Java-based API built by contributors of this chapter. MASPower uses negotiation functions to judge the value of an issue based on available resources, e.g. money, time or maintenance scheduling. A social rational can also be used in developing a matrix that defines the balance between individual (local) or social (global) responsibilities. Chapter 5 provides a detailed description of a multi-agent incident and event diagnosis technique, where intelligent agents interrogate the supervisory control and data acquisition system (SCADA) and digital fault recorders (DFR) for alarm and fault information, which is interpreted and reacted to by control response. The Protection Engineering Diagnostic Agent (PEDA) design utilizes a Foundation for Intelligent Physical Agents (FIPA) Agents Communication Language (ACL) communications and messaging structure. Social interactions between agents are achieved through the development of agent wrappers, allowing for autonomy of execution. Chapter 6 provides a description of a restoration architecture that is based on bus agents and facilitator agents, again separating local operations from global or supervisory operations, respectively. From this perspective, the architecture seeks the best method at restoring a power path after a fault. Chapter 7 introduces a simulation tool, designated the Electrical Power and Communications Synchronizing Simulator (EPOCHS), simulated several power and communication systems scenarios for testing performance using the multi-agent structure. Notably, the EPOCHS software interfaces with well-known simulators, including PSCAD/EMTDC, for electromagnetic simulation, PSLF, for electromechanical transient simulation and NS2, for network communication. Three categories of simulation were performed, utilizing high speed communication to show reduced clearing times for faults, time-stamped differential measurements for determining status and frequency stabilization using generator rejection. Multi-agent interactions can include, for instance, communications between multiple smart relay or protection devices. Chapter 8 frames the meshed structure as global, regional and local. As expected, global control provides slower, global coordination through set points to the regional and local agents, where faster response is required. Both single-input single-output (SISO) and multiple-input single-output (MISO) control designs for multi-agent control systems are outlined, using a state feedback optimal design for reduced order models. The MISO system utilizes additional available data to improve the robustness of the control design. Chapter 9 introduces the autonomous control of Flexible AC Transmission Systems (FACTS) unified power flow controller (UPFC), which although they provide good power flow control can also negatively impact the steady-state operation due to short response times. The UPFC design uses proportional-integral controllers for reactive power control, active power control and voltage control. Building on the autonomous model of Chapter 1, the contributor designed a management and coordination scheme to counteract these negative influences based on fuzzy and integral controllers. Chapter 10 describes how multi-agent interactions with FACTS devices with a common objective can be used to resolve issues such as voltage regulation. These interactions, depicted with finite state machine graphics, show how a global objective can be attained through multi-agent coordination. Situational awareness is key to the decision and evaluation process, and visualization of a global system view as compared to traditional data display is an important factor. Chapter 11, diagrams the methods for characterizing a power system through intelligent agents and presentation of information that specify the events, effects and actions being performed by the power system to provide a more user friendly human machine interface. Chapter 12 discusses the concept of meshed control from the perspective of the Strategic Power Infrastructure Defense (SPID) program being conducted by the Advanced Power Technologies (APT) Consortium. The meshed structure is categorized as the Deliberative, Coordination and Reactive layers, covering global to local considerations, respectively. In brief the Deliberation layer considers system planning and vulnerabilities, the Coordination ensures a current picture of the power system is maintained, and the Reactive performs direct interactions with field devices and sensors, including fault protection and isolation. Diagrammed within this architecture are the use of DER for reliability of local systems and methods to effectively island areas as isolation from propagation of faults, or to isolate the grid from a fault area. The contributor for Chapter 13 proposes a multi-agent structure called Flexible, Reliable and Intelligent Delivery System (FRIENDS). This approach uses an agent termed a quality control center (QCC) that controls the power supplied to its own loads by power quality and importance, and communicates with other QCCs that perform the same function. When a fault occurs, a message is propagated from the affected QCC that may require it to isolate from the distribution system but may or may not also request other QCCs to pick up load that was isolated if it is no longer able to supply it with its distributed generation. Multi-agent QCC relationships are suggested for voltage control, which utilize autonomous reactive power regulation devices or by rearranging the topology of the QCC with static switches, the former requiring a decentralized control requiring only inter-agent intercommunications and the latter requiring a centralized control to maintain an optimal global perspective. The decentralized approach provided a notable improvement. This work provides many perspectives with a common focus of using a multi-agent or meshed approach for intelligent design of reliable, self-healing power systems. This topic has seen a lot of discussion in recent literature, using various soft computing, statistical and heuristic techniques 1-7. The author characterizes several of the concerns, such as restoration and situational awareness, with a practical approach that engineers in the field can use as a basis for future designs. The graduate student in the power area would also benefit from the guidance given, and aid in the development of this recent technological area.