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3rd International Workshop on Software Engineering Challenges for the Smart Grid (SE4SG 2014), June 1, 2014, Hyderabad, India

SE4SG 2014 – Proceedings

Contents - Abstracts - Authors

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

Title Page

Message from the Chairs
We would like to take this opportunity to welcome you to the third international workshop on Software Engineering Challenges for the Smart Grid (SE4SG 2014) on June 1st 2014, co-located with ICSE 2014 in Hyderabad, India. The workshop focuses on understanding and identifying the unique challenges and opportunities for Software Engineering (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 highly demanding problem domain for software engineers to address. The objective of this workshop is to bring together members of the software engineering community and the power engineering community to understand these requirements and determine the most appropriate software engineering tools, methods, and techniques.
A Modeling Method to Develop Goal-Oriented Adaptive Agents in Modeling and Simulation for Smart Grids
Hyo-Cheol Lee, Hee-Soo Kim, and Seok-Won Lee
(Ajou University, South Korea)
Agent-based modeling and simulation is a useful method to analyze and predict the complex and dynamic behavior of a smart grid which consists of diverse stakeholders and components such as devices, services and policies. A smart grid adaptively behaves in its dynamically changed environment and evolves over time as introducing new components and modifying (or removing) the existing components. Therefore, the model of the grid also has to be adaptive and evolutionary for users to obtain meaningful analysis. In this work, we propose a goal-oriented modeling and simulation framework to systematically model and simulate an adaptive and evolutionary smart grid. In this framework, we concentrate on the activity to design agents for the grid. This activity is based on a goal-oriented organizational agent model which goal-oriented requirement language, belief-desire-intention architecture and agent-group-role model are integrated into. This model helps modelers to design adaptive agents from their simulation requirements and to revise their models with the already developed agents like as a smart grid evolves. Further, we demonstrate the benefits of our modeling method in designing agents for a simulation scenario where a virtual power plant shares profit with its distributed energy resources in a smart grid.
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Demand Response Algorithm Incorporating Electricity Market Prices for Residential Energy Management
Arun G. Nair and Batchu Rajasekhar
(IIT Gandhinagar, India)
Demand Side Energy Management has now been established in the smart grid framework in order to meet the fluctuating demand-supply gap that exists mainly during peak load periods. Along with the potential of energy efficiency and conservation measures, due to the increasing use of domestic appliances in a developing country like India, Demand Response (DR) has gained a lot of importance in the residential sector. Most of the DR algorithms that have been developed mostly focus on energy consumption scheduling without considering electricity market prices. In this paper we have proposed a DR algorithm for residential consumers in India, which can be used to optimally schedule appliances, making use of actual day-ahead electricity market price data and also considering user preferences in the operation of appliances. The algorithm has been simulated for five different consumers using a flat pricing scheme and two time-differentiated pricing schemes. For each customer, an estimated saving of 6% can be obtained by using hourly pricing. Analysis of the results underlines the importance of formulating effective dynamic pricing policies for successful implementation of DR algorithms for the residential users thereby tapping into the vast DR potential that exists in India.
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SmartDSM: A Layered Model for Development of Demand Side Management in Smart Grids
Fahad Javed, Usman Ali, Muhammad Nabeel, Qasim Khalid, Naveed Arshad, and Jahangir Ikram
(GIFT University, Pakistan; University of Management and Technology Lahore, Pakistan; Lahore University of Management Sciences, Pakistan)
Growing power demand and carbon emissions is motivating utility providers to introduce smart power systems. One of the most promising technology to deliver cheaper and smarter electricity is demand side management. A DSM solution controls the devices at user premises in order to achieve overall goals of lower cost for consumer and utility. To achieve this various technologies from different domains come in to play from power electronics to sensor networks to machine learning and distributed systems design. The eventual system is a large, distributed software system over a heterogeneous environment and systems. Whereas various algorithms to plan the DSM schedule have been proposed, no concerted effort has been made to propose models and architectures to develop such a complex software system. This lack of models provides for a haphazard landscape for researchers and practitioners leading to confused requirements and overlapping concerns of domains. This was observed by the authors in developing a DSM system for their lab and faculty housing. To this end in this paper we present a model to develop software systems to deliver DSM. In addition to the model, we present a road map of software engineering research to aid development of future DSM systems. This is based on our observations and insights of the developed DSM systems.
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