No abstract

Microgrids are an increasingly common component of the evolving electricity grids with the potential to improve local reliability, reduce costs, and increase penetration rates for distributed renewable generation. The additional complexity of microgrids often leads to increased investment costs, creating a barrier for widespread adoption. These costs may result directly from specific needs for islanding detection, protection systems and power quality assurance that would otherwise be avoided in simpler system configurations. However, microgrids also facilitate additional value streams that may make up for their increased costs and improve the economic viability of microgrid deployment. This paper analyses the literature currently available on research relevant to value streams occurring in microgrids that may contribute to offset the increased investment costs. A review on research related to specific microgrid requirements is also presented.

No abstract

This paper provides an introduction to cyber attack impact analysis in the smart grid and highlights existing research in the field. We present an impact analysis framework where we focus on the model synthesis stage where both cyber and physical grid entity relationships are modelled as directed graphs. Each node of the graph has associated state information that is governed by dynamical system equations that model the physics of the interaction (for electrical grid components) or functionality (for cyber grid elements). We illustrate how cause-effect relationships can be conveniently expressed for both analysis and extension to large-scale smart grid systems.

Security issues in cyber-physical systems are of paramount importance due to the often safetycritical nature of its associated applications. A first step in understanding how to protect such systems requires an understanding of emergent weaknesses, in part, due to the cyber-physical coupling. In this paper, we present a framework that models a class of cyber-physical switching vulnerabilities in smart grid systems. Variable structure system theory is employed to effectively characterize the cyber-physical interaction of the smart grid and demonstrate how existence of the switching vulnerability is dependent on the local structure of the power grid. We identify and demonstrate how through successful cyber intrusion and local knowledge of the grid an opponent can compute and apply a coordinated switching sequence to a circuit breaker to disrupt operation within a short interval of time. We illustrate the utility of the attack approach empirically on the Western Electricity Coordinating Council three-machine, nine-bus system under both model error and partial state information.INDEX TERMS Cyber-physical systems, security modeling, variable structure systems, coordinated switching attacks.

Microgrid operations are challenging due to variability in loads and renewable energy generation. Advanced tools capable of taking uncertainty into account are essential to maximize microgrid benefits when operating microgrid owned DERs. This paper proposes a novel optimization model for day-ahead economic dispatch of flexible resources within a microgrid environment, considering uncertainty of PV and loads.This model is conceived to support the microgrid supervisory control layer, providing a security-constrained day-ahead strategy to operate three types of microgrid flexible resources: PV, electric storage and controllable loads. The work presented in this paper introduces a novelty in microgrid operations by presenting a stochastic version of the day ahead scheduling of microgrid DERs to deal with uncertainties associated with PV, load and temperature while considering microgrid network limits and end-user comfort as optimization constraints. An annual analysis quantifies the benefits of to the microgrid-owner of a stochastic formulation over a deterministic one both in terms of ensuring end-user comfort and decreasing operation costs.

No abstract

Distributed power systems in the U.S. and globally are evolving to provide reliable and clean energy to consumers. In California, existing regulations require significant increases in renewable generation, as well as identification of customer-side distributed energy resources (DER) controls, communication technologies, and standards for interconnection with the electric grid systems. As DER deployment expands, customer-side DER control and optimization will be critical for system flexibility and demand response (DR) participation, which improves the economic viability of DER systems. Current DER systems integration and communication challenges include leveraging the existing DER and DR technology and systems infrastructure, and enabling optimized cost, energy and carbon choices for customers to deploy interoperable grid transactions and renewable energy systems at scale. This paper presents a cost-effective solution to these challenges by exploring communication technologies and information models for DER system integration and interoperability. This system uses open standards and optimization models for resource planning based on dynamic-pricing notifications and autonomous operations within various domains of the smart grid energy system. It identifies architectures and customer engagement strategies in dynamic DR pricing transactions to generate feedback information models for load flexibility, load profiles, and participation schedules. The models are tested at a real site in California-Fort Hunter Liggett (FHL). The results for FHL show that the model fits within the existing and new DR business models and networked systems for transactive energy concepts. Integrated energy systems, communication networks, and modeling tools that coordinate supply-side networks and DER will enable electric grid system operators to use DER for grid transactions in an integrated system.