Background: Energy informatics (EI) is the area of research that addresses the application of technology to resolve complex problems in the energy domain. Goebel et al. (BISE 6:25-31, 2014) provided an EI research framework to encompass all aspects of EI research. Due to rapid EI improvements, many current research areas have not been incorporated into this framework. Specifically, this research posits that grid reliability is an underrepresented research area and should be incorporated into the framework. The rapidly changing nature of energy generation, and new developments in the electric-power network, are driving the need for grid reliability research. The goal of this paper is to extend the EI research framework offered by the Goebel et al. through a systematic review of current literature. Methods: This literature review includes current publications (2015)(2016)(2017) in power utility and technical reference libraries together with the earlier foundational EI papers. Results: The systematic literature review is based on a broad automated search of appropriate digital sources (IEEE Xplore and the Web of Science) using relevant search terms. The paper also details the components of grid reliability research as well as their accompanying use cases. Conclusion: The expanded EI research framework presented in this literature review should help researchers identify areas for future research endeavors. In the extended EI research framework, service reliability is now included as a third research component adding to the existing energy efficiency and renewable-energy supply components. BackgroundEnergy informatics (EI) research concerns the use of information and communication technologies to address energy challenges (Watson and Boudreau 2011) and to inform the application of technology to resolve complex problems in the energy domain. The U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy (2017) classified challenges within the electricity-grid domain into two types: (1) transmission-system challenges and (2) distribution-system challenges. Transmissionsystem challenges include grid operations, grid reliability, grid stability, models and codes, grid operators, and utilities. Distribution-system challenges includes voltage and volt-ampere reactivity regulation, unintentional islanding, power quality, protection coordination, distribution modeling, visibility and control, codes, and standards. Goebel et al. (2014) stated that energy efficiency and renewable-energy supply are the two principal types of research movements within the energy domain. Energy efficiency research involves studying individual incentives and behavioral dynamics to influence electricity consumers' usage behavior. This first type drives the evolution of smart energy-saving systems. The second type of research, renewable-energy supply, seeks to resolve challenges arising in the integration of such renewable sources of energy as wind and solar power into the electric grid. This, in turn drives, the advancement of sma...

Integration of electric vehicles (EVs) into the smart grid has attracted considerable interest from researchers, governments, and private companies alike. Such integration may bring problems if not conducted well, but EVs can be also used by utilities and other industry stakeholders to enable the smart grid. This paper presents a systematic literature review of the topic and offer a research framework to guide future research and enrich the body of knowledge. The systematic literature review presented in this paper does not contain all the material available on this subject. It does, however, include most of the key publications readily available in a power-utility or technical-reference library together with some of the earlier papers in the field (the anchor papers). For this review, we selected appropriate digital sources (digital libraries and indexing systems; IEEE Xplore and Web of Science), determined the search terms, and conducted a broad automated search. This article also details the components of the research theme—EV integration into the smart grid—as well as its accompanying use cases. The analysis of the relevant papers indicated four types of key research concerns: power-grid, power-system, and smart-grid reliability and the impacts of changes on them. These results can help guide future research to further smart-grid development. Future research can also expand the reach of this research to address its limitations in scope and depth.

United States electric utility industry is moving toward a new power grid that will accommodate bi-directional energy flow and the incorporation of Distributed Energy Resources (DERs). Currently, utility companies lack tools to identify locations on the electric grid that can sustain DERs' adoption. This research explores the use of Geographic Information Systems (GIS), a class of tools for developing spatial models, with the aim of optimizing the placement of DERs. The intent of this research paper is to propose a Geographic Decision Support Systems (GDSS) model as a solution for the utility industry to assist in the DERs' portfolio choices and provide actionable information for utilities, system operators, and power producers. Claremont city has been chosen as the research site to demonstrate the applicability of the proposed model. This will also serve as the basis for future research.

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The U.S. electric-power infrastructure urgently needs renovation. Recent major power outages in California, New York, Texas, and Florida have highlighted U.S. electric-power unreliability. The media have discussed the U.S. aging power infrastructure and the Public Utilities Commission has demanded a comprehensive review of the causes of recent power outages. This paper explores geographic information systems (GIS) and a spatially enhanced predictive power-outage model to address: How may spatial analytics enhance our understanding of power outages? To answer this research question, we developed a spatial analysis framework that utilities can use to investigate power-failure events and their causes. Analysis revealed areas of statistically significant power outages due to multiple causes. This study’s GIS model can help to advance smart-grid reliability by, for example, elucidating power-failure root causes, defining a data-responsive blackout solution, or implementing a continuous monitoring and management solution. We unveil a novel use of spatial analytics to enhance power-outage understanding. Future work may involve connecting to virtually any type of streaming-data feed and transforming GIS applications into frontline decision applications, showing power-outage incidents as they occur. GIS can be a major resource for electronic-inspection systems to lower the duration of customer outages, improve crew response time, as well as reduce labor and overtime costs.