System Design, Economic Analysis and Operation Strategy of a Campus Microgrid

Arzani, Ali; Boshoff, S.; Arunagirinathan, Paranietharan; Maigha, Maigha; Enslin, J.H.R.

doi:10.1109/pedg.2018.8447652

Cited by 8 publications

(22 citation statements)

References 8 publications

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“…• Campus microgrids are studied to depict the different types of sources installed at various campuses, including conventional energy resources, renewable energy sources, demand-side management (DSM), and energy storage systems (ESSs); • Campus microgrids are reviewed based on optimization techniques, objective functions (OFs), and modeling techniques; • Campus microgrids are studied as innovative campus microgrid scenarios that serve as smart decision approaches for university campuses. Campus/Building [4] University of Cyprus (UCY) [39] Clemson University, South Carolina…”

Section: Introductionmentioning

confidence: 99%

“…It also provides a new solution for different power plants. This paper discusses various power Campus [6] University of Malta [39] Clemson University, South Carolina…”

mentioning

confidence: 99%

“…It also covered a timeline of 5 years of technological development, including aspects from 2014 up to the latest microgrid developments. It also provides a new solution for a microgrid that operates for [39] Clemson University, South Carolina…”

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confidence: 99%

“…This will also facilitate researchers in their respe areas and optimize the microgrid with the updated energy management systems [46 methodology monitored the power flow information in real time, monitored energy sumption, and stabilized the campus microgrid's energy [47]. It also covered a timel 5 years of technological development, including aspects from 2014 up to the lates Energies 2021, 14, x FOR PEER REVIEW [39] Clemson University, South Carolina…”

mentioning

confidence: 99%

“…This will also facilitate researchers i areas and optimize the microgrid with the updated energy management methodology monitored the power flow information in real time, monit sumption, and stabilized the campus microgrid's energy [47]. It also cov 5 years of technological development, including aspects from 2014 up Energies 2021, 14, x FOR PEER REVIEW [39] Clemson University, South Carolina…”

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confidence: 99%

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An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges

Muqeet¹,

Munir

Javed

et al. 2021

Energies

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The multiple uncertainties in a microgrid, such as limited photovoltaic generations, ups and downs in the market price, and controlling different loads, are challenging points in managing campus energy with multiple microgrid systems and are a hot topic of research in the current era. Microgrids deployed at multiple campuses can be successfully operated with an exemplary energy management system (EMS) to address these challenges, offering several solutions to minimize the greenhouse gas (GHG) emissions, maintenance costs, and peak load demands of the microgrid infrastructure. This literature survey presents a comparative analysis of multiple campus microgrids’ energy management at different universities in different locations, and it also studies different approaches to managing their peak demand and achieving the maximum output power for campus microgrids. In this paper, the analysis is also focused on managing and addressing the uncertain nature of renewable energies, considering the storage technologies implemented on various campuses. A comparative analysis was also considered for the energy management of campus microgrids, which were investigated with multiple optimization techniques, simulation tools, and different types of energy storage technologies. Finally, the challenges for future research are highlighted, considering campus microgrids’ importance globally. Moreover, this paper is expected to open innovative paths in the future for new researchers working in the domain of campus microgrids.

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Section: Introductionmentioning

confidence: 99%

“…It also provides a new solution for different power plants. This paper discusses various power Campus [6] University of Malta [39] Clemson University, South Carolina…”

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges

Muqeet¹,

Munir

Javed

et al. 2021

Energies

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Ethical Frameworks for Machine Learning in Sensitive Healthcare Applications

Javed,

Muqeet,

Javed

et al. 2024

IEEE Access

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The application of Machine Learning (ML) in healthcare has opened unprecedented avenues for predictive analytics, diagnostics, and personalized medicine. However, the sensitivity of healthcare data and the ethical dilemmas associated with automated decision-making necessitate a rigorous ethical framework. This review paper aims to provide a comprehensive overview of the existing ethical frameworks that guide ML in healthcare and evaluates their adequacy in ad-dressing ethical challenges. Specifically, this article offers an in-depth examination of prevailing ethical constructs that oversee healthcare ML, spotlighting pivotal concerns: data protection, in-formed assent, equity, and patient autonomy. Various analytical approaches including quantitative metrics, statistical methods for bias detection, and qualitative thematic analyses are applied to address these challenges. Insights are further enriched through case studies of Clinical Decision Support Systems, Remote Patient Monitoring, and Telemedicine Applications. Each case is evaluated against existing ethical frameworks to identify limitations and gaps. Based on our com-prehensive review and evaluation, we propose actionable recommendations for evolving ethical guidelines. The paper concludes by summarizing key findings and underscoring the urgent need for robust ethical frameworks to guide ML applications in sensitive healthcare environments. Future work should focus on the development and empirical validation of new ethical frameworks that can adapt to emerging technologies and ethical dilemmas in healthcare ML.

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