72 research outputs found
Capturing Distribution Grid-Integrated Solar Variability and Uncertainty Using Microgrids
The variable nature of the solar generation and the inherent uncertainty in
solar generation forecasts are two challenging issues for utility grids,
especially as the distribution grid integrated solar generation proliferates.
This paper offers to utilize microgrids as local solutions for mitigating these
negative drawbacks and helping the utility grid in hosting a higher penetration
of solar generation. A microgrid optimal scheduling model based on robust
optimization is developed to capture solar generation variability and
uncertainty. Numerical simulations on a test feeder indicate the effectiveness
of the proposed model.Comment: IEEE Power and Energy Society General Meeting, 201
Distribution Market Clearing and Settlement
There are various undergoing efforts by system operators to set up an
electricity market at the distribution level to enable a rapid and widespread
deployment of distributed energy resources (DERs) and microgrids. This paper
follows the previous work of the authors in implementing the distribution
market operator (DMO) concept, and focuses on investigating the clearing and
settlement processes performed by the DMO. The DMO clears the market to assign
the awarded power from the wholesale market to customers within its service
territory based on their associated demand bids. The DMO accordingly settles
the market to identify the distribution locational marginal prices (DLMPs) and
calculate payments from each customer and the total payment to the system
operator. Numerical simulations exhibit the merits and effectiveness of the
proposed DMO clearing and settlement processes.Comment: 2016 IEEE Power & Energy Society General Meetin
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Effects of Solar and Wind Generation Integration on Feeder Hosting Capacity
With the increased penetration of distributed generation (DG) utilities are beginning to see impacts on their system, especially on the ability of a feeder to accommodate DG. In this paper we introduce a stochastic simulation framework to assess the effects on hosting capacity from solar and wind generation for various loading scenarios. The general approach includes the use of a k-means clustering algorithm for segmenting and grouping the raw wind, solar, and load data to define patterns and assign probabilities to each pattern. Monte Carlo simulations are adopted for calculating probabilistic outcomes for a variety of wind, solar, and load scenarios, with the use of a distribution planning software. The outcomes of the simulations, i.e., statistics of minimum and maximum feeder hosting capacity, are used to derive their probability distribution functions (pdfs). The pdfs of the minimum and maximum hosting capacity provide insights into the effects on loading from various wind and solar DG scenarios. The proposed framework is illustrated for a representative utility feeder
Resource curse and institutional quality in oil countries
The examination of the relationship between oil resources and economic growth reveals that oil curse in oil countries is not reliable and these countries can be divided into countries with poor and rich institutions. In the first group, oil revenues have a negative and significant effect on the economic growth; in the second group, oil revenues have a positive and significant effect on economic growth. In other words, what causes curse or blessing of oil resources is the institution qualities of the countries; the lower the institution quality, the more negative effect of the oil revenues on the economic growth. In this article we derive the kink point of institutional index whereby oil revenues effect on the economic growth changes from positive to negative
Resource curse and institutional quality in oil countries
The examination of the relationship between oil resources and economic growth reveals that oil curse in oil countries is not reliable and these countries can be divided into countries with poor and rich institutions. In the first group, oil revenues have a negative and significant effect on the economic growth; in the second group, oil revenues have a positive and significant effect on economic growth. In other words, what causes curse or blessing of oil resources is the institution qualities of the countries; the lower the institution quality, the more negative effect of the oil revenues on the economic growth. In this article we derive the kink point of institutional index whereby oil revenues effect on the economic growth changes from positive to negative
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Current Data Gaps in Modeling Essential Worker Absenteeism Due to COVID-19
With the uncertain physical and mental health implications of COVID-19 infection, companies have taken a myriad of actions that aim to reduce the risk of employees contracting the virus, with most grounded in reducing or eliminating in-person interactions. Our preliminary analysis indicates that while there is some data to support modelling absenteeism, there are gaps in the available evidence, requiring the use of assumptions that limit precision and efficacy for decision support. Improved data on time-to-recovery after hospitalization, absenteeism due to family or other household member illness, and mental health’s impact on returning to work will support the development of more robust absenteeism models and analytical approaches
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