Review and Perspectives on Data Sharing and Privacy in Expanding Electricity Access

Lee, Jonathan T.; Freitas, João F. G. de; Ferrall, Isa; Kammen, Daniel M.; Brewer, Eric; Callaway, Duncan S.

doi:10.1109/jproc.2019.2919306

Cited by 11 publications

(6 citation statements)

References 40 publications

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“…They note that standardization and transparency into the reliability of electricity products allows individuals to make the most informed decision. This transparency allows for increased competition between providers resulting in better services provided for end users and allows governments, investors, and development institutions to encourage the best performing systems through performance-based regulation and investment (Lee et al 2019). This article study demonstrates the possibilities and insight gained when full detailed data is available, however rare.…”

Section: Discussionmentioning

confidence: 90%

“…These are necessary, but not sufficient, first steps towards understanding the full landscape of electricity reliability from which future work can find where simplifications are, or are not, appropriate. Lee et al (2019) details the opportunities and risks for key stakeholders from increased data sharing in the context of expanding electricity access. They note that standardization and transparency into the reliability of electricity products allows individuals to make the most informed decision.…”

Section: Discussionmentioning

confidence: 99%

“…Their concerns can be partially attributed to the poor quality of the first products to enter these markets, as well as counterfeit products, (GOGLA 2019, Saini et al 2019) but there remains a troubling lack of quantification of the reliability and service quality of DRE writ large. An absence of transparency, standards, and reporting persists across the off-grid solar sector (Practical Action 2014, Yaqoot et al 2016) despite efforts such as Lighting Global's solar product verification program, 'resulting in huge discrepancies in reported metrics and mistrust among stakeholders' (Lee et al 2019). 'Technical reliability studies are rare K even though service quality analyses would be important to help in capturing the full potential of these systems in the future' (Numminen and Lund 2019).…”

Section: Context and Gapsmentioning

confidence: 99%

See 2 more Smart Citations

Measuring the reliability of SDG 7: the reasons, timing, and fairness of outage distribution for household electricity access solutions

Ferrall

Callaway

Kammen

2022

Environ. Res. Commun.

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The United Nations identifies ensuring “access to affordable, reliable, sustainable and modern energy for all” as one of its Sustainable Development Goals for 2030. This article focuses on the comparatively under-investigated question of reliability within the broader goal. We empirically study experienced household electricity reliability using common frameworks in key countries such as Tanzania, Kenya, and India. Datasets represent a diverse set of technologies including solar home systems (SHS), solar pico-grids, and national electricity grids. First, the prevailing reliability metrics - SAIDI and SAIFI – are measured for all datasets. Informed by critical assessments, this article then proposes a suite of new metrics that facilitate improved reliability comparisons by considering the reasons, timing, and fairness of outage distribution. Analyses using our proposed metrics reveal key policy implications for addressing energy poverty in the Global South. Acknowledging that the systems studied provide different capacity, affordability, and carbon footprints, we find that on average, SHS provided comparable hours of lighting to local grid connections, however SHS outages were less equally distributed than those from other sources. In addition, calculations of grid reliability were highly sensitive to measurement techniques and assumptions used, necessitating high resolution data for policy decisions. Finally, economically driven outages conspicuous in pre-paid SHS systems (i.e., disconnections for non-payment) composed a significant portion of experienced unreliability. These findings quantify the important contribution of demand-side affordability to experienced household reliability, thereby allowing for a comprehensive understanding of the reliability of SDG 7.

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Section: Discussionmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Section: Context and Gapsmentioning

confidence: 99%

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Measuring the reliability of SDG 7: the reasons, timing, and fairness of outage distribution for household electricity access solutions

Ferrall

Callaway

Kammen

2022

Environ. Res. Commun.

Self Cite

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“…In Ref. [2], the authors present a review of the current data sharing policies within the electric industry, highlighting several severe limitations as well as the value of increased collaboration. Similarly, the authors of [3] argue that power system data need to be open and accessible in order to facilitate higher quality research and more effective policy solutions to tackle the challenges of an evolving grid.…”

Section: Introductionmentioning

confidence: 99%

Generation of synthetic multi‐resolution time series load data

2023

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The availability of large datasets is crucial for the development of new power system applications and tools; unfortunately, very few are publicly and freely available. The authors designed an end‐to‐end generative framework for the creation of synthetic bus‐level time‐series load data for transmission networks. The model is trained on a real dataset of over 70 Terabytes of synchrophasor measurements spanning multiple years. Leveraging a combination of principal component analysis and conditional generative adversarial network models, the developed scheme allows for the generation of data at varying sampling rates (up to a maximum of 30 samples per second) and ranging in length from seconds to years. The generative models are tested extensively to verify that they correctly capture the diverse characteristics of real loads. Finally, an opensource tool called LoadGAN is developed which gives researchers access to the fully trained generative models via a graphical interface.

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“…Unfortunately, one of the recognized issues which is hindering this process is the lack of widely available datasets of real power system measurements and data. In [2], the authors present a review of the current data sharing policies within the electric industry, highlighting several severe limitations as well as the value of increased collaboration. Similarly, the authors of [3] argue that power system data needs to be open and accessible in order to facilitate higher quality research and more effective policy solutions to tackle the challenges of an evolving grid.…”

Section: Introductionmentioning

confidence: 99%

Generation of Synthetic Multi-Resolution Time Series Load Data

Pinceti¹,

Sankar²,

Kosut³

2021

Preprint

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The availability of large datasets is crucial for the development of new power system applications and tools; unfortunately, very few are publicly and freely available. We designed an end-to-end generative framework for the creation of synthetic bus-level time-series load data for transmission networks. The model is trained on a real dataset of over 70 Terabytes of synchrophasor measurements spanning multiple years. Leveraging a combination of principal component analysis and conditional generative adversarial network models, the scheme we developed allows for the generation of data at varying sampling rates (up to a maximum of 30 samples per second) and ranging in length from seconds to years. The generative models are tested extensively to verify that they correctly capture the diverse characteristics of real loads. Finally, we develop an opensource tool called LoadGAN which gives researchers access to the fully trained generative models via a graphical interface.

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Review and Perspectives on Data Sharing and Privacy in Expanding Electricity Access

Abstract: This article discusses the gathering and use of grid and end-user data, and examines how expanding access to data and data-sharing are likely to provide value and pose risks to key energy-access stakeholders.

Cited by 11 publications

References 40 publications

Measuring the reliability of SDG 7: the reasons, timing, and fairness of outage distribution for household electricity access solutions

Measuring the reliability of SDG 7: the reasons, timing, and fairness of outage distribution for household electricity access solutions

Generation of synthetic multi‐resolution time series load data

Generation of Synthetic Multi-Resolution Time Series Load Data

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