Igor Kaitovic

Virtual Power Plant As a Bridge between Distributed Energy Resources and Smart Grid

The liberalization of energy markets, especially in correlation with the Smart Grid concept development, requires adjusted legislation, new business models, energy stock exchanges establishment and many other advanced instruments. Realization of these features necessitates novel concepts to support such changes in the power system while granting security and reliability of supply. Such evolution poses new challenges to ICT (Information and Communication Technologies) to bridge the gap between increased complexity of deregulated market and on the other side expected rapid growth of number of players in power systems. Increasing presence of Distributed Energy Resources (DER) implementations constitutes a further source of complexity.Bearing in mind ongoing and possible scenarios we aim to determinate the place and role of the novel Virtual Power Plants (VPP) concept, related to the Smart Grid structure. At the same time we introduce an innovative modeling approach as an instrument to determine actors and highlight their actual roles and interactions from different point of view, trying to pave the way for development of a common understanding platform for variety of stakeholders. The effectiveness of the proposed modeling concept is shown through a number of UML models representing system level description of VPP at different levels of abstraction.

Adoption of model-driven methodology to aggregations design in Smart Grid

Economical and environmental concerns push toward novel solutions for sustainable, renewable and intelligent energy power grid — the Smart Grid. Such complex system, or better aggregation of systems, involve a number of various stakeholders coming from different areas of expertise, requires novel ICT solutions, etc. Even so, on-going projects do not apply unique formal design methodology and language. In order to better correlate the projects, improve understating of system requirements and simplify system design by decomposing its complexity a model-driven methodology (MDM) and SysML could be applied. Applying MDM should give a possible referent model for aggregations in future Power Grid

Optimizing Failure Prediction to Maximize Availability

Availability of autonomous systems can be enhanced with self-monitoring and fault-tolerance methods based on failures prediction. With each correct prediction, proactive actions may be taken to prevent or to mitigate a failure. On the other hand, incorrect predictions will introduce additional downtime associated with the overhead of a proactive action that may decrease availability. The total effect on availability will depend on the quality of prediction (measured with precision and recall), the overhead of proactive actions (penalty), and the benefit of proactive actions when prediction is correct (reward). In this paper, we quantify the impact of failure prediction and proactive actions on steady-state availability. Furthermore, we provide guidelines for optimizing failure prediction to maximize availability by selecting a proper precision and recall trade-off with respect to penalty and reward. A case study to demonstrate the approach is also presented.

Proactive Failure Management in Smart Grids for Improved Resilience: A Methodology for Failure Prediction and Mitigation

A gradual move in the electric power industry towards Smart Grids brings several challenges to the system operation such as preserving its resilience and ensuring security. As the system complexity grows and a number of failures increases, the need for grid management paradigm shift from reactive to proactive is apparent and can be realized by employing advanced monitoring instruments, data analytics and prediction methods. In order to improve resilience of the Smart Grid and to contribute to efficient system operation, we present a blueprint of a comprehensive methodology for proactive failure management that may also be applied to manage other types of disturbances and undesirable changes. The methodology is composed of three main steps: continuous monitoring of the most indicative features; prediction of failures; their mitigation. The approach is complementary to the existing ones that are mainly based on fast detection and localization of grid disturbances, and reactive corrective actions.

A Model for Evaluation of User-Perceived Service Properties

An ever-increasing number of both functional and non-functional requirements has resulted in growing system complexity which demands for new solutions in system modeling and evaluation. As a remedy, service-oriented architecture (SOA) proposes services as basic building elements of system design. Service dependability is highly dependent on the properties of the underlying information and communications technology (ICT) infrastructure. This is especially true for the user-perceived dependability of a specific pair service client and provider as every pair can utilize different ICT components. We provide a model for the description of ICT components and their non-functional properties based on the Unified Modeling Language (UML). Given a service description, a network topology model and a pair service client and provider, we propose a methodology to automatically identify relevant ICT components and generate a user-perceived service infrastructure model (UPSIM). We demonstrate the feasibility of the methodology by applying it to parts of the service network infrastructure at University of Lugano (USI), Switzerland. We then show how this methodology can be used to facilitate user-perceived service dependability analysis.

Virtual metering for Virtual PHEV aggregation

Technically sustainable solutions for integration of (PH)EVs in Smart Grid emerge as an important concern. We discuss the need for introduction of Virtual Aggregations supported by implementation of Virtual Meters in power system structures. We advocate our proposal with an evaluation of scenarios based on realistic data. The structure and functionalities of the Virtual Aggregator, as well as proposed enhancements on the Smart Grid side, are presented.

Functional requirements of embedded systems for monitoring and control structure of Virtual Power Plants

Efficient integration of distributed renewable generation into a reliable single entity in technical and commercial terms is one of key issues for successful realization of smart-grids. The novel concept of Virtual Power Plants (VPP) emerges to be promising response to these needs. ICT is enabling technology for VPP implementation. An efficient monitoring and control system coupled with appropriate communication structure must be designed in a scalable and modular way so that full interoperability among components of the system is achieved. On top of that, Control Center applications take care of power flow optimization (production, consumption, ancillary services etc.) and high-level applications (e.g. energy trading, Demand Side Management etc.). In this work we focus on functional requirements for realization of such concept by means of embedded systems.

A framework for disturbance analysis in smart grids by fault injection

With growing complexity of electric power systems, a total number of disturbances is expected to increase. Analyzing these disturbances and understanding grid’s behavior, when under a disturbance, is a prerequisite for designing methods for boosting grid’s stability. The main obstacle to the analysis is a lack of relevant data that are publicly available. In this paper, we present a design and implementation of a framework for emulation of grid disturbances by employing simulation and fault-injection techniques. We also present a case study on generating voltage sag related data. A foreseen usage of the framework considers mainly prototyping, root-cause analysis as well as design and comparison of methods for disturbance detection and prediction.

Modeling Requirements for Security-enhanced Design of Embedded Systems

Designing an embedded system is a complex process that involves working on both hardware and software. The first step in the design process is defining functional and non-functional requirements; among them, it is fundamental to also consider security. We propose an effective way for designers to specify security requirements starting from User Security Requirements. User Security Requirements are high-level requirements related to security attacks that the system should be able to withstand. We also provide a mechanism to automatically translate these User Requirements into System Security Requirements, that include a detailed description of security solutions. For expressing requirements we use Unified Modeling Language (UML); specifically, we create a UML profile to describe user requirements and we use model-to-model transformation to automatically generate system requirements. We show the effectiveness of the modeling scheme and of the translation mechanism by applying our methodology to a case study based on wearable devices for e-health monitoring.

Systems Engineering for Assessment of Virtual Power System Implementations

In this work we present an adoption of systems engineering methodology for design and assessment of a Virtual Power System (VPS). The VPS has been defined as an aggregation of distributed energy resources, consumers and storages which can operate autonomously, and is presented to the power system as a single unit in technical and commercial terms. The complexity of these critical systems is tackled by means of systems engineering. We have applied our approach in scope of a research project AlpEnergy.