2019
DOI: 10.1109/access.2019.2958275
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Model Driven Software Engineering of Power Systems Applications: Literature Review and Trends

Abstract: This paper presents a survey on Software Engineering techniques for the power systems area. Our goal is to identify tools and techniques that can improve the life cycle management of customized applications for Energy Management Systems (SCADA/EMS), by applying a Model Driven Engineering (MDE) approach. We conducted a systematic literature review of published works related to the design and development of such applications. Two main repositories of publications in the area were used as sources and four search … Show more

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Cited by 16 publications
(9 citation statements)
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References 56 publications
(93 reference statements)
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“…Especially the integration of the electric power system with other domains (thermal, gas, water/waste water, transportation etc.) into a smart energy system requires additional efforts which are [12,13]:…”
Section: Discussionmentioning
confidence: 99%
“…Especially the integration of the electric power system with other domains (thermal, gas, water/waste water, transportation etc.) into a smart energy system requires additional efforts which are [12,13]:…”
Section: Discussionmentioning
confidence: 99%
“…Generally, most of the works are focused on the field of health, medicine, oncology, etc. and references to the field of engineering greatly limit the scope of the research [28][29][30][31][32][33]. In some sources, the search was limited to two work vectors, as we have planned in this study, to subsequently establish the databases or search repositories chosen.…”
Section: Methodsmentioning
confidence: 99%
“…The literature review presented in (Neis et al 2019) summarizes the state of the art of MBSE in software engineering for power systems applications. Even though the targeted research questions aim to reveal how source models are processed into target models or code, none of the approaches mentioned produce fully functional software applications.…”
Section: Related Workmentioning
confidence: 99%
“…Activity 3: Language Family Identification. The literature review in (Neis et al 2019) investigated, among others, a research question regarding which modeling languages are used in model-driven and generative approaches of applications in the power systems domain. The languages found are classified into different language categories.…”
Section: Related Workmentioning
confidence: 99%