Denise M. Case

Goal-Based Holonic Multiagent System for Operation of Power Distribution Systems

Large-scale integration of rooftop solar power generation is transforming traditionally passive power distribution systems into active ones. High penetration of such devices creates new dynamics for which the current power distribution systems are inadequate. The changing paradigm of power distribution system requires it to be operated as cyber-physical system. A goal-based holonic multiagent system (HMAS) is presented in this paper to achieve this objective. This paper provides details on design of the HMAS for operation of power distribution systems. Various operating modes and associated goals are discussed. Finally, the role of HMAS is demonstrated for two applications in distribution systems. The first one is associated with control of reactive power at solar photovoltaic installations at individual homes for optimal operation of the system. The second deals with the state estimation of the system leveraging different measurements available from smart meters at homes.

Applying an O-MaSE Compliant Process to Develop a Holonic Multiagent System for the Evaluation of Intelligent Power Distribution Systems

This paper describes the application of an Organization-based Multiagent System Engineering O-MaSE compliant process to the development of a holonic multiagent system MAS for testing control algorithms for an intelligent power distribution system. The paper describes the Adaptive O-MaSE AO-MaSE process, which provides architects and developers a structured approach for testing and iteratively adding functionality in complex, adaptive systems. The paper describes the holonic MAS architecture for the intelligent power distribution system, the challenges encountered while developing the holonic architecture, the lessons learned during the project, and demonstrates how the application of the process enhanced project development.

Fuzzy Cognitive Map to model project management problems

Project management is a complex process impacted by numerous factors either from the external environment and/or internal factors completely or partially under the project managers control. Managing projects successfully involves a complex amalgamation of comprehensive, informed planning, dynamic assessment and analysis of changes in external and internal factors, and the development and communication of updated strategies over the life of the project. Project management involves the interaction and analysis of many systems and requires the continuous integration and evaluation of large amounts of information. Fuzzy Cognitive Maps (FCM) allow us to encode project management knowledge and experiential results to create a useful model of the interacting systems. This paper covers the representation and development of a construction project management FCM that provides an integrated view of the most important concepts affecting construction project management and risk management. This paper then presents the soft computing approach of FCM to project management (PM) modeling and analysis. The resulting PM-FCM models the interaction of internal and external factors and offers an abstract conceptual model of interacting concepts for construction project management application.

Scaffolding Version Control into the Computer Science Curriculum.

Version control systems (VCS) are widely-used in the software industry. They provide a powerful, collaborative framework that allows software engineers to work together effectively. VCS allow users to track changes and merge ongoing work into concurrently evolving software projects. Distributed VCS such as Git, allow a great degree of flexibility, and provide powerful options for managing personal code and evolving collaborative content. Power incurs responsibility, and introducing collaborative coding and version control tools to new developers can create many challenges. Yet these tools, once mastered, are crucial skills for professional developers. In this paper, the authors introduce VCS to computer science students both in a custom environment specifically designed to support new developers and in a commercially-available native environment suitable for more experienced students. Results show that proper introduction of these powerful tools can make early exposure a positive and valued experience.

VeCVL: A Visual Language for Version Control.

Version control systems (VCS), such as Subversion and Git, are pervasive in industry; they are invaluable tools for collaborative development that allow software engineers to track changes, monitor issues, merge work from multiple people, and manage releases. These tools are most effective when they are a part of a developer’s habitual workflow. Unfortunately, the use of these powerful tools is often taught much later in a developer’s educational career than other tools like programming languages or databases. Even an experienced student’s first experience with version control can be unpleasant. In this paper, the authors analyze the workflow of two common Version Control Systems with different version controls (Subversion and Git) to build a common visual language for these systems (Version Control Visual Language, or VeCVL), and show that the same visual language applies to other version control systems. Keywordscomputer science education, education technology, pedagogy, version control, visual language

Using fuzzy cognitive maps to model university desirability and selection

Predicting the desirability and number of student applications to universities is a challenging and dynamic undertaking. Student applications are affected by a variety of factors ranging from those related to the university itself and its surrounding community, to factors up to the national level, including perceptions of international relations. This paper proposes a way of modeling this complex task and the related decision-making using fuzzy cognitive maps (FCM). The process includes determination of the key concepts and factors affecting the desirability of a university for a representative set of cohort groups. Cohort groups allow us to reuse model concepts and linguistic variables while customizing the relationships to create a custom, dynamic model based on a variety of target population subsets. This paper introduces a reusable process for developing models based on cohort groups, and presents three customized FCM models that can be used to explore a range of possibilities and provide a FCM model for prediction and planning concerning university desirability and selection.

Introducing a Fuzzy Cognitive Map for modeling power market auction behavior

The power market is becoming more complex as independent small producers are entering it but their energy offerings are often based on alternative sources which may be dependent on transient weather conditions. Power market auction behavior is a typical large-scale system characterized by huge amounts of data and information that have to be taken into consideration to make decisions. Fuzzy Cognitive Maps (FCM) offer a method for using the knowledge and experience of domain experts to describe the behavior of a complex system. This paper discusses FCM representation and development, and describes the use of FCM to develop a behavioral model of the system. This paper then presents the soft computing approach of FCM for modeling complex power market behavior. The resulting FCM models a variety of factors that affect individual participant behaviors during power auctions and provides an abstract conceptual model of the interacting entities for a specific case problem.