SE4SG 2014 - 3rd International Workshop on Software Engineering Challenges for the Smart Grid

The emerging smart grid is incorporating intelligence into power distribution networks. A smart grid provides the capabilities to handle the challenges of increasing complexity in the power grid, to respond to demand growth, support renewable energy sources and satisfy the requirements for enhanced, adaptive service quality. Achieving these goals requires a framework for the cohesive integration of communication and information technologies, interconnected in a complex energy and information real-time control network. This framework must provide the principle properties of smart grids, including self-healing, availability and responsiveness to demand and supply variability.
The realization of smart grid benefits requires a major sustained effort from the power and software industry. This effort must deliver advanced software solutions. Collectively, these emerging solutions pose a broad range of software engineering (SE) challenges, creating the need for members of the SE research community to interact with the power engineering community and other communities. This workshop will facilitate such collaboration. Participants will be able to share perspectives and present findings from research and practice relevant to smart grid software and services.
Call for Papers
This 3rd workshop will focus on understanding and identifying the unique challenges and opportunities for SE to contribute to and enhance the design and development of the smart grid. In smart grids, the geographical scale, requirements on real-time performance and reliability, and diversity of application functionality all combine to produce a unique, highly demanding problem domain for SE to address. The objective of this workshop is to bring together members of the SE community and the power engineering community to understand these requirements and determine the most appropriate SE tools and methods.
Topics of Interest
SE4SG workshop is interested in submissions on all topics related to identifying and developing appropriate methods, tools and techniques for smart grid software. Specifically, we will focus on:
Applications that support power engineering operations. Such applications include, but are not limited to, event processing systems for managing and manipulating large amounts of real-time sensor data, and systems that provide infrastructure for metering, analysis, decision support and control;
Software and enterprise architectures tailored for smart grids, including the challenges of the Smart Grid as an ultra-large-scale system
The need for designing applications with advanced computing capabilities. This requires understanding the implications of, for example, exploiting cloud computing and high performance, multicore computing platforms for computationally intensive smart grid functions;
Designing analytic-numeric/simulation frameworks targeting smart grids. These can model designs and quantify system properties, such as responsiveness and availability, based on predictive (numerical, simulated) and historical data.
Methodologies that apply advanced SE approaches to analyze and improve the properties of smart grid applications. These include model-driven development, self-managing and adaptive software systems, and quality reasoning and evaluation frameworks.
Employing best practices for Requirements Engineering and V&V in smart grid. This includes considering the synergy between requirements and architectures in such a critical ultra-large-scale system.
Standards-based distributed architecture solutions and reference architectures that enable open interfaces with plug-and-play hardware and software components.
The design and analysis of robust, scalable security and privacy frameworks for the smart grid.
Approaches to modeling and monitoring the system-wide performance, scalability and/or other quality properties of the smart grid software framework.
SE approaches for business-IT alignment for smart grids
Integrating smart grid topics into SE curriculums at teaching institutes
Novel architectures for software systems supporting energy trading and business decisions in the context of smart grids
Lessons learned and experience from successful application of smart grid industry standards in software systems
Computational intelligence in smart grids