This chapter presents a cyber-physical reference model for smart grid. Most of the early smart grid applications have been developed in an ad-hoc manner, without any underlying framework. The proposed reference model addresses this issue and enables the design of smart grid as a robust system that is extensible to the future. The proposed reference model is based on service-oriented computing paradigm and is compatible with the existing service-oriented technologies, used in enterprise computing, such as Web Services. However, it also extends these technologies for handling the hard real-time aspects of smart grid by introducing resource-aware service deployment and quality-of-service (QoS)-aware service monitoring phases. According to the proposed reference model, each smart grid scenario is characterized by three elements: (1) an application model that describes the smart grid applications to be supported by the system as a set of resource- and QoS-aware service descriptions, (2) a platform model that describes the smart grid platform as a set of computing nodes, communication links, sensors, actuators, and power system entities, and (3) a set of algorithms that enable resource-aware service deployment, QoS-aware service discovery, and QoS-aware service monitoring. This chapter also presents typical development steps of a smart grid application according to the proposed referencemodel. Moreover, this chapter identifies a number of technological requirements that can enable the development of smart grid applications according to the proposed reference model. Although the development of these required technologies is a topic of ongoing research, this chapter identifies some potential solution approaches, based on state-of-the-art techniques from realtime systems literature. The case study of a demand response application has been employed to explain the various aspects of the proposed smart grid reference model.
CITATION STYLE
Tariq, M. U., Grijalva, S., & Wolf, M. (2014). A service-oriented, cyber-physical reference model for smart grid. Power Systems, 79, 25–42. https://doi.org/10.1007/978-3-662-45928-7_2
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