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Robert Hyndman is the author of the forecast package in R. I’ve been using the package for long-term time series forecasts. The package comes with some built in methods for plotting forecast data objects in R that Ive wanted to customize for improved clarity and presentation. The following article achieves that goal and shares two scripts for plotting forecast data objects using ggplot.
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Dubai Electricity and Water Authority (DEWA) has achieved another world record. This week, DEWA awarded a 700MW project priced at AED14.2 billion (US$3,86 billion). The project is the fourth phase of the Mohammed bin Rashid Al Maktoum Solar Park. The award is the largest single-site Concentrated Solar Power (CSP) project in the world. It is also the largest CSP project based on the IPP model. The contract is awarded to a consortium comprising Saudi Arabia’s ACWA Power and China’s Shanghai Electric.
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CAISO time-of-day power prices are changing. The daily price profile now reflects a growing premium in the morning and evening hours, The profile also includes a steeper price discount in the midday hours. The new time-of-day prices represent a market incentive: ramp power supply up or down more quickly on command.
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The Western EIM (Energy Imbalance Market) is an interregional exchange that is gaining ground as CAISO adopts a larger share of renewable energy production.
What is the Western EIM?
Grid operators use the EIM’s advanced market systems to find the lowest-cost energy to serve real-time customer demand across a wide geographic area. EIM provides transparency on the status of multiple grids.
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For the first time, U.S. wind and solar production in March exceeded 10% of total electricity generation, based on March data in EIA’s Electric Power Monthly.
The record contribution for non-hydro renewables comes amid surging installations of both wind and solar in the US, with 14.8GW of solar and 8.2GW of wind added in 2016. On an annual basis, wind and solar made up 7% of total U.S. electric generation.
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Posted in Data, Solar, Wind
Design engineering of solar power system includes inverter sizing. Optimal inverter sizing must consider how much DC power will be produced by the solar array and how much AC power the inverter is able to output (its power rating). Appropriate sizing will typically allow DC production greater than the AC power rating. This article explains why inverter clipping or production curtailments help to maximize total power output
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The linear model is the most widely used data science tools and one of the most important. In addition, there is another basic tool known as the nearest neighbor method (NN). Both models can be used to go beyond prediction for classification. Feature classes are used by machines to recognize faces within a crowd, to “read” road signs by distinguishing one letter from another, and to set voter registration districts by separating population groups. This article applies and compares both classification methods
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The Dubai Electricity and Water Authority (DEWA) will build the first hydroelectric power station in the GCC. DEWA will build a 250-MW pumped storage facility powered by solar PV.
HE Saeed Mohammed Al Tayer, MD and CEO of DEWA, announced the project. HH Sheikh Mohammed bin Rashid Al Maktoum, Vice President and Prime Minister of the UAE and Ruler of Dubai was also present.
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Technology progress is a key to solar growth and pricing. By extension, the ability to model technology progress is essential to understanding future energy supply and demand.
Solar innovation is widespread. Examples include solar cell efficiency, module manufacturing, and learning innovations with solar system installation and operation. Solar pricing and growth are also supported by innovations in enabling technology, such as battery storage, smart grids and electric vehicles.
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Best subset regression is an technique for model building and variable selection. The method looks at all combinations of independent predictor variables for use in a multiple regression model. Model developers and analysts will often struggle with variable selection, especially when the number of predictors is high. Ideally, each set of predictors is run and the best set is selected using a criteria for model performance. The following article provides custom functions for best subset selection that are fast and easy to use.
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A new method to extract data tables from PDF files is introduced. Most of the data scraping tools available are browser-based. The common tools are also manual in nature and limited to one table at a time. A solution is outlined to extract multiple tables at once. The solution combines the R programming language with the open-source Java program Tabula. The result is a convenient method that transforms documents into databases.
The ability to train a machine to extract data tables from PDF files has several benefits:
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A solar inverter is a key component in a grid-tied solar power system. There are 3 types of grid tied inverters – central, string and micro inverters. This article defines how an inverter works and compares the advantages and disadvantages of each inverter type.
What is an inverter?
An inverter converts the direct current (DC) from a generator into alternating current (AC) for grid and appliance use.
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A common task in spatial data analysis is extracting SpatialPoints inside a set of polygons or buffer zones. Analysts can use standard GIS or map tools to extract a set of points within an area of interest using manual “point-and-click” routines. This method is easy, but will probably prove impractical, especially in cases involving big data. The alternative is to train a machine to automatically extract the points in a polygon or buffer zone. This post achieves that task and presents a case-study with R code.
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