The new grid needs more flexibility to be able to operate with so much uncertainty. The flexibility is a very fuzzy concept and being used very loosely in the industry. It has to be formalized to be utilized in control and design algorithms. An attempt of such formalization is presented later in this paper.
The industry is also very imprecise about the control architecture of the grid. Many different definitions of the control architecture are being used: centralized/ decentralized, hierarchical, coordinated, hierarchical-coordinated, distributed, collaborative, cooperative, holonic, etc. All these terms are not clearly defined even in the control theory literature and, in our opinion, require special attention from the control community. Today’s control seems to be strictly hierarchical and centralized. Such system is very rigid and has very little room for flexibility. With the increasing complexity, such an approach is insufficient to maintain system reliability and resilience. Changing only the grid architecture to provide more flexibility while maintaining reliability, is not sufficient. In order to reduce complexity, we have to make control system flexible as well, with the ability to adapt to different system states. This is impossible without some degree of distributed decision making and decentralized control adapting to unknown and dynamic environments. Additionally, decentralized systems are more resilient to disturbances or faults. These new qualities could be achieved by implementing distributed cooperative control paradigm with the capability of assembling temporary control entities collaborating in addressing specific events. Such a capability would allow decomposing a very complicated control problem into smaller, more manageable tasks. Large percentage of the system events are developing slowly enough so the corrective control would be capable of addressing large number of events. A new generation of state monitoring systems should be developed to take advantage of new information available from different devices and sensors. Decentralized control also requires careful design of the standard communication and control protocols and interfaces to enable interaction among heterogeneous components while cooperating in solving common problems.
The increase of the computational capabilities and new IT architectures create opportunities for implementation of innovative control algorithms and infrastructure. Rapidly evolving cloud technology introduces unprecedented capabilities for on-line cooperation and collaboration. Being accessible from geographically wide areas and capable of high performance computing, cloud could serve as a medium for decentralized and distributed decision making and control. The tremendous flexibility of this computing infrastructure will very quickly transition from very simple to highly complex control problems as needed. A simple example of such problem: resolving anticipated imbalance caused by a major contingency with the help of neighboring systems:
• Assembling model on the fly
• Communicating coordination constraints (max imbalance allowed by participating entities).
• Once resolved, the temporary collaborator is dropped.
Another benefit is the ability to capture, accumulate and use patterns of the best control actions and strategies making it available during future events–stigmergy.
The system of such complexity also requires a different approach to reliability. Being under stress most of the time, power grid has to develop a survivability property, which is more general than just reliability. In addition, new reliability criteria together with resilience have to be investigated and implemented in order to formalize the objective of the power system control and required constraints.
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