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

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

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